Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone disease.Methods:A comprehensive lit...Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone disease.Methods:A comprehensive literature review was performed using PubMed,Scopus,and Google Scholar databases to identify publications about innovative concepts or supporting applications of AI in the improvement of every medical procedure relating to stone disease.The terms“endourology”,“artificial intelligence”,“machine learning”,and“urolithiasis”were used for searching eligible reports,while review articles,articles referring to automated procedures without AI application,and editorial comments were excluded from the final set of publications.The search was conducted from January 2000 to September 2023 and included manuscripts in the English language.Results: A total of 69 studies were identified.The main subjects were related to the detection of urinary stones,the prediction of the outcome of conservative or operative management,the optimization of operative procedures,and the elucidation of the relation of urinary stone chemistry with various factors.Conclusion: AI represents a useful tool that provides urologists with numerous amenities,which explains the fact that it has gained ground in the pursuit of stone disease management perfection.The effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing data.However,little is known concerning the potential of this vast field.Electronic patient records,containing big data,offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms.Nevertheless,the existing applications are not generalizable in real-life practice,and high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.展开更多
Objective:To evaluate the feasibility and the safety of medial non-papillary percutaneous nephrolithotomy(npPCNL)for the management of large proximal ureteral stones.Methods:We evaluated prospectively collected data o...Objective:To evaluate the feasibility and the safety of medial non-papillary percutaneous nephrolithotomy(npPCNL)for the management of large proximal ureteral stones.Methods:We evaluated prospectively collected data of 37 patients with large proximal ureteral stones more than 1.5 cm in diameter treated by prone npPCNL.Depending on stone size,in-toto stone removal or lithotripsy using the Lithoclast®Trilogy(EMS Medical,Nyon,Switzerland)was performed.Perioperative parameters including operative time(from start of puncture to the skin suturing),stone extraction time(from the first insertion of the nephroscope to the extraction of all stone fragments),and the stone-free rate were evaluated.Results:Twenty-one males and 16 females underwent npPCNL for the management of large upper ureteral calculi.The median age and stone size of treated patients were 58(interquartile range[IQR]:51-69)years and 19.3(IQR:18.0-22.0)mm,respectively.The median operative time and stone extraction time were 25(IQR:21-29)min and 8(IQR:7-10)min,respectively.One case(2.7%)of postoperative bleeding and two cases(5.4%)of prolonged fever were managed conservatively.The stone-free rate at a 1-month follow-up was 94.6%.Conclusion:The npPCNL provides a straight route to the ureteropelvic junction and proximal ureter.Approaching from a dilated portion of the ureter under low irrigation pressure with larger diameter instruments results in effective and safe stone extraction within a few minutes.展开更多
BACKGROUND Several studies have explored the long-term prognosis of patients with asymp-tomatic gallbladder stones.These reports were primarily conducted in facilities equipped with beds for addressing symptomatic cas...BACKGROUND Several studies have explored the long-term prognosis of patients with asymp-tomatic gallbladder stones.These reports were primarily conducted in facilities equipped with beds for addressing symptomatic cases.AIM To report the long-term prognosis of patients with asymptomatic gallbladder stones in clinics without bed facilities.METHODS We investigated the prognoses of 237 patients diagnosed with asymptomatic gallbladder stones in clinics without beds between March 2010 and October 2022.When symptoms developed,patients were transferred to hospitals where appropriate treatment was possible.We investigated the asymptomatic and survival periods during the follow-up.RESULTS Among the 237 patients,214(90.3%)remained asymptomatic,with a mean asymptomatic period of 3898.9279±46.871 d(50-4111 d,10.7 years on average).Biliary complications developed in 23 patients(9.7%),with a mean survival period of 4010.0285±31.2788 d(53-4112 d,10.9 years on average).No patient died of biliary complications.CONCLUSION The long-term prognosis of asymptomatic gallbladder stones in clinics without beds was favorable.When the condition became symptomatic,the patients were transferred to hospitals with beds that could address it;thus,no deaths related to biliary complications were reported.This finding suggests that follow-up care in clinics without beds is possible.展开更多
Hepatolithiasis(HL)poses a significant risk for cholangiocarcinoma(CCA)development,with reported incidences ranging from 5%-13%.Risk factors include older age,smoking,hepatitis B infection,and prolonged HL duration.Ch...Hepatolithiasis(HL)poses a significant risk for cholangiocarcinoma(CCA)development,with reported incidences ranging from 5%-13%.Risk factors include older age,smoking,hepatitis B infection,and prolonged HL duration.Chronic inflammation and mechanical stress on the biliary epithelium contribute to CCA pathogenesis.Hepatectomy reduces CCA risk by removing stones and atrophic liver segments.However,residual stones and incomplete removal increase CCA risk.Kim et al identified carbohydrate antigen 19-9,carcinoembryonic antigen,and stone laterality as CCA risk factors,reaffirming the importance of complete stone removal.Nonetheless,challenges remain in preventing CCA recurrence post-surgery.Longer-term studies are needed to elucidate CCA risk factors further.展开更多
Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utili...Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings.展开更多
The artificial photosynthesis technology has been recognized as a promising solution for CO_(2) utilization.Photothermal catalysis has been proposed as a novel strategy to promote the efficiency of artificial photosyn...The artificial photosynthesis technology has been recognized as a promising solution for CO_(2) utilization.Photothermal catalysis has been proposed as a novel strategy to promote the efficiency of artificial photosynthesis by coupling both photochemistry and thermochemistry.However,strategies for maximizing the use of solar spectra with different frequencies in photothermal catalysis are urgently needed.Here,a hierarchical full-spectrum solar light utilization strategy is proposed.Based on this strategy,a Cu@hollow titanium silicalite-1 zeolite(TS-1)nanoreactor with spatially separated photo/thermal catalytic sites is designed to realize high-efficiency photothermal catalytic artificial photosynthesis.The space-time yield of alcohol products over the optimal catalyst reached 64.4μmol g−1 h−1,with the selectivity of CH3CH2OH of 69.5%.This rationally designed hierarchical utilization strategy for solar light can be summarized as follows:(1)high-energy ultraviolet light is utilized to drive the initial and difficult CO_(2) activation step on the TS-1 shell;(2)visible light can induce the localized surface plasmon resonance effect on plasmonic Cu to generate hot electrons for H2O dissociation and subsequent reaction steps;and(3)low-energy near-infrared light is converted into heat by the simulated greenhouse effect by cavities to accelerate the carrier dynamics.This work provides some scientific and experimental bases for research on novel,highly efficient photothermal catalysts for artificial photosynthesis.展开更多
Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on p...Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.展开更多
Plankton are an important component of marine protected areas(MPAs),and its communities would require much smaller interpatch distances to ensure connection among MPAs.According to the survey from MPAs dominated by ar...Plankton are an important component of marine protected areas(MPAs),and its communities would require much smaller interpatch distances to ensure connection among MPAs.According to the survey from MPAs dominated by artificial reefs and adjacent waters(estuary area(EA),aquaculture area(AA),artificial reef area(ARA),natural area(NA)and comprehensive effect area(CEA))in Haizhou Bay in spring and autumn,we analyzed phyto-zooplankton composition,abundance and biomass,and correlation with hydrologic variables to gain information about the forces that structure the plankton.The results showed that the dominant zooplankton were copepods(spring,98.9%;autumn,94.2%),while the phytoplankton were mainly composed of Bacillariophyta(spring,61.8%;autumn,95.6%).The RDA results showed that temperature,salinity and depth highly associated with the distribution and composition of plankton species among the habitats than other factors in spring;temperature,Chla and DO had the strongest influence in autumn.The zooplankton in the ARA and AA ecosystems basically contained the same species as those in other habitats,and each habitat also exhibited a relatively unique combination of plankton species.The structures of the EA zooplankton in spring and the EA phytoplankton in both seasons were much different than other habitats,which may have been caused by factors such as currents and tides.We concluded that there exists similarity of the plankton community between artificial reef area and adjacent waters,whereas the EAs may be relatively independent systems.Therefore,these interaction between plankton community should be considered when designing MPA networks,and ocean circulations should be considered more than the environmental factors.展开更多
Phase change materials (PCMs) can be incorporated with low-cost minerals to synthesize composites for thermal energy storage in building applications.Stone coal (SC) after vanadium extraction treatment shows potential...Phase change materials (PCMs) can be incorporated with low-cost minerals to synthesize composites for thermal energy storage in building applications.Stone coal (SC) after vanadium extraction treatment shows potential for secondary utilization in composite preparation.We prepared SC-based composite PCMs with SC as a matrix,stearic acid (SA) as a PCM,and expanded graphite (EG) as an additive.The combined roasting and acid leaching treatment of raw SC was conducted to understand the effect of vanadium extraction on promoting loading capacity.Results showed that the combined treatment of roasting at 900℃ and leaching increased the SC loading of the composite by 6.2%by improving the specific surface area.The loading capacity and thermal conductivity of the composite obviously increased by 127%and 48.19%,respectively,due to the contribution of 3wt% EG.These data were supported by the high load of 66.69%and thermal conductivity of 0.59 W·m^(-1)·K-1of the designed composite.The obtained composite exhibited a phase change temperature of 52.17℃,melting latent heat of 121.5 J·g^(-1),and good chemical compatibility.The SC-based composite has prospects in building applications exploiting the secondary utilization of minerals.展开更多
Background: The growth and use of Artificial Intelligence (AI) in the medical field is rapidly rising. AI is exhibiting a practical tool in the healthcare industry in patient care. The objective of this current review...Background: The growth and use of Artificial Intelligence (AI) in the medical field is rapidly rising. AI is exhibiting a practical tool in the healthcare industry in patient care. The objective of this current review is to assess and analyze the use of AI and its use in orthopedic practice, as well as its applications, limitations, and pitfalls. Methods: A review of all relevant databases such as EMBASE, Cochrane Database of Systematic Reviews, MEDLINE, Science Citation Index, Scopus, and Web of Science with keywords of AI, orthopedic surgery, applications, and drawbacks. All related articles on AI and orthopaedic practice were reviewed. A total of 3210 articles were included in the review. Results: The data from 351 studies were analyzed where in orthopedic surgery. AI is being used for diagnostic procedures, radiological diagnosis, models of clinical care, and utilization of hospital and bed resources. AI has also taken a chunk of share in assisted robotic orthopaedic surgery. Conclusions: AI has now become part of the orthopedic practice and will further increase its stake in the healthcare industry. Nonetheless, clinicians should remain aware of AI’s serious limitations and pitfalls and consider the drawbacks and errors in its use.展开更多
AIM:To assess the efficacy of artificial natural light in preventing incident myopia in primary school-age children.METHODS:This is a prospective,randomized control,intervention study.A total of 1840 students from 39 ...AIM:To assess the efficacy of artificial natural light in preventing incident myopia in primary school-age children.METHODS:This is a prospective,randomized control,intervention study.A total of 1840 students from 39 classes in 4 primary schools in Foshan participated in this study.The whole randomization method was adopted to include classes as a group according to 1:1 randomized control.Classrooms in the control group were illuminated by usual light,and classrooms in the intervention group were illuminated by artificial natural light.All students received uncorrected visual acuity and best-corrected visual acuity measurement,non-cycloplegic autorefraction,ocular biometric examination,slit lamp and strabismus examination.Three-year follow-up,the students underwent same procedures.Myopia was defined as spherical equivalent refraction≤-0.50 D and uncorrected visual acuity<20/20.RESULTS:There were 894 students in the control group and 946 students in the intervention group with a mean±SD age of 7.50±0.53y.The three-year cumulative incidence rate of myopia was 26.4%(207 incident cases among 784 eligible participants at baseline)in the control group and 21.2%(164 incident cases among 774 eligible participants at baseline)in the intervention group[difference of 5.2%(95%CI,3.7%to 10.1%);P=0.035].There was also a significant difference in the three-year change in spherical equivalent refraction for the control group(-0.81 D)compared with the intervention group[-0.63 D;difference of 0.18 D(95%CI,0.08 to 0.28 D);P<0.001].Elongation of axial length was significantly different between in the control group(0.77 mm)and the intervention group[0.72 mm;difference of 0.05 mm(95%CI,0.01 to 0.09 mm);P=0.003].CONCLUSION:Artificial natural light in the classroom of primary schools can result in reducing incidence rate of myopia during a period of three years.展开更多
Pacific oyster(Crassostrea gigas)is one of the most important mollusks cultured all around the world.Selective breeding programs of Pacific oysters in China is initiated since 2006 and developed the genetically improv...Pacific oyster(Crassostrea gigas)is one of the most important mollusks cultured all around the world.Selective breeding programs of Pacific oysters in China is initiated since 2006 and developed the genetically improved strain with fast-growing trait.However,little is known about the metabolic signatures of the fast-growing trait.In the present study,the non-targeted metabolomics was performed to analyze the metabolic signatures of adductor muscle tissue in one-year old Pacific oysters from fast-growing strain and the wild population.A total of 7767 and 10174 valid peaks were extracted and quantified in ESI^(+)and ESI^(−)modes,resulting in 399 and 381 annotated metabolites,respectively.PCA and OPLS-DA revealed that considerable separation among samples from fastgrowing strain and wild population,suggesting the differences in metabolic signatures.Meanwhile,81 significantly different metabolites(SDMs)were identified in the comparisons between fast-growing strain and wild population,based on the strict thresholds.It was found that there were highly correlation and conserved coordination among these SDMs.KEGG enrichment analysis indicated that the SDMs were tightly related to pantothenate and CoA biosynthesis,steroid hormone biosynthesis,riboflavin metabolism,and arginine and proline metabolism.Of them,the CoA biosynthesis and metabolism,affected by pantetheine and pantothenic acid,might be important for the growth of Pacific oysters under artificial selective breeding.The study provides the comprehensive views of metabolic signatures in response to artificially selective breeding,and is helpful to better understand the molecular mechanism of fastgrowing traits in Pacific oysters.展开更多
The research investigated the adoption of artificial intelligence (AI) technol-ogies among agricultural entrepreneurs in Ondo state, Nigeria. A purposive sample of 120 participants involved in agriculture was selected...The research investigated the adoption of artificial intelligence (AI) technol-ogies among agricultural entrepreneurs in Ondo state, Nigeria. A purposive sample of 120 participants involved in agriculture was selected for the study. Socioeconomic characteristics analysis revealed that the mean age of the re-spondents was 48.3 years. A majority (77%) of the respondents were male, and approximately 68% were married. Regarding education, 32.5% had completed secondary education, while 32.5% had tertiary education. The av-erage annual income was 1,166,800 naira, with a significant proportion (71.7%) identifying as Christians. The study found a significant association between respondents’ awareness levels and their adoption of AI-enabled technologies (χ<sup>2</sup> = 7.714, p = 0.005). Based on these findings, it is recom-mended that extension officers receive training in the latest agricultural technologies, including those enabled by AI. Furthermore, the study suggests the introduction of easily accessible and user-friendly AI technologies to farmers to enhance their productivity and income with minimal or no cost implications.展开更多
Global health (GH) aims to improve healthcare for all people on the planet and eradicate all avoidable diseases and deaths. The inception of Artificial Intelligence (AI) is innovating healthcare practices and improvin...Global health (GH) aims to improve healthcare for all people on the planet and eradicate all avoidable diseases and deaths. The inception of Artificial Intelligence (AI) is innovating healthcare practices and improving patient outcomes by shuffling enormous volumes of health data—from health records and clinical studies to genetic information analyzing it much faster than humans. AI also helps in the improvement of medical imaging and medical diagnosis. There is an increased optimism regarding the use of applications of AI locally but can these facets be translated globally in the advancement and delivery of healthcare with the help of AI. At present majority of AI developments and applications in health care provide to the needs of developed countries and there is little effort to develop programs which could help to improve healthcare delivery globally. We performed this narrative review to assess the difficulties and discrepancies in implementing AI in global health delivery and find ways to improve.展开更多
Objective: To explore the application value of rapid rehabilitation concept in patients with extrahepatic bile duct stones under laparoscopy during perioperative period. Methods: 90 patients with extrahepatic bile duc...Objective: To explore the application value of rapid rehabilitation concept in patients with extrahepatic bile duct stones under laparoscopy during perioperative period. Methods: 90 patients with extrahepatic bile duct stones treated in our hospital from January 2022 to February 2023 were selected as the research object and randomly divided into the study group and the control group. The control group was given routine care, and the observation group was given rapid surgical rehabilitation care. The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time, hospitalization time and complication rate were compared between the two groups. The independent sample T test was used for the measurement data, and the x<sup>2</sup> test was used for the counting data, and the difference was statistically significant (P Results: The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time and hospitalization time in the study group were shorter than those in the control group (all P Conclusion: The concept of rapid rehabilitation can significantly improve the perioperative nursing effect of patients with extrahepatic bile duct stones and accelerate their rehabilitation, which is worth improving and popularizing.展开更多
In this editorial we comment on the article“Potential and limitations of ChatGPT and generative artificial intelligence in medial safety education”published in the recent issue of the World Journal of Clinical Cases...In this editorial we comment on the article“Potential and limitations of ChatGPT and generative artificial intelligence in medial safety education”published in the recent issue of the World Journal of Clinical Cases.This article described the usefulness of artificial intelligence(AI)in medial safety education.Herein,we focus specifically on the use of AI in the field of pain medicine.AI technology has emerged as a powerful tool,and is expected to play an important role in the healthcare sector and significantly contribute to pain medicine as further developments are made.AI may have several applications in pain medicine.First,AI can assist in selecting testing methods to identify causes of pain and improve diagnostic accuracy.Entry of a patient’s symptoms into the algorithm can prompt it to suggest necessary tests and possible diagnoses.Based on the latest medical information and recent research results,AI can support doctors in making accurate diagnoses and setting up an effective treatment plan.Second,AI assists in interpreting medical images.For neural and musculoskeletal disorders,imaging tests are of vital importance.AI can analyze a variety of imaging data,including that from radiography,computed tomography,and magnetic resonance imaging,to identify specific patterns,allowing quick and accurate image interpretation.Third,AI can predict the outcomes of pain treatments,contributing to setting up the optimal treatment plan.By predicting individual patient responses to treatment,AI algorithms can assist doctors in establishing a treatment plan tailored to each patient,further enhancing treatment effectiveness.For efficient utilization of AI in the pain medicine field,it is crucial to enhance the accuracy of AI decision-making by using more medical data,while issues related to the protection of patient personal information and responsibility for AI decisions will have to be addressed.In the future,AI technology is expected to be innovatively applied in the field of pain medicine.The advancement of AI is anticipated to have a positive impact on the entire medical field by providing patients with accurate and effective medical services.展开更多
Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce...Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce. Aim: To test a novel AI commercially available tool for image analysis on a series of laparoscopic scenes. Methods: The research tools included OPENAI CHATGPT 4.0 with its corresponding image recognition plugin which was fed with a list of 100 laparoscopic selected snapshots from common surgical procedures. In order to score reliability of received responses from image-recognition bot, two corresponding scales were developed ranging from 0 - 5. The set of images was divided into two groups: unlabeled (Group A) and labeled (Group B), and according to the type of surgical procedure or image resolution. Results: AI was able to recognize correctly the context of surgical-related images in 97% of its reports. For the labeled surgical pictures, the image-processing bot scored 3.95/5 (79%), whilst for the unlabeled, it scored 2.905/5 (58.1%). Phases of the procedure were commented in detail, after all successful interpretations. With rates 4 - 5/5, the chatbot was able to talk in detail about the indications, contraindications, stages, instrumentation, complications and outcome rates of the operation discussed. Conclusion: Interaction between surgeon and chatbot appears to be an interesting frontend for further research by clinicians in parallel with evolution of its complex underlying infrastructure. In this early phase of using artificial intelligence for image recognition in surgery, no safe conclusions can be drawn by small cohorts with commercially available software. Further development of medically-oriented AI software and clinical world awareness are expected to bring fruitful information on the topic in the years to come.展开更多
Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based algorit...Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based algorithms.In this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and decision-making.Federated Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data effectively.In this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare systems.The experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)platform.The experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.展开更多
●AIM:To quantify the performance of artificial intelligence(AI)in detecting glaucoma with spectral-domain optical coherence tomography(SD-OCT)images.●METHODS:Electronic databases including PubMed,Embase,Scopus,Scien...●AIM:To quantify the performance of artificial intelligence(AI)in detecting glaucoma with spectral-domain optical coherence tomography(SD-OCT)images.●METHODS:Electronic databases including PubMed,Embase,Scopus,ScienceDirect,ProQuest and Cochrane Library were searched before May 31,2023 which adopted AI for glaucoma detection with SD-OCT images.All pieces of the literature were screened and extracted by two investigators.Meta-analysis,Meta-regression,subgroup,and publication of bias were conducted by Stata16.0.The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool.●RESULTS:Twenty studies and 51 models were selected for systematic review and Meta-analysis.The pooled sensitivity and specificity were 0.91(95%CI:0.86–0.94,I2=94.67%),0.90(95%CI:0.87–0.92,I2=89.24%).The pooled positive likelihood ratio(PLR)and negative likelihood ratio(NLR)were 8.79(95%CI:6.93–11.15,I2=89.31%)and 0.11(95%CI:0.07–0.16,I2=95.25%).The pooled diagnostic odds ratio(DOR)and area under curve(AUC)were 83.58(95%CI:47.15–148.15,I2=100%)and 0.95(95%CI:0.93–0.97).There was no threshold effect(Spearman correlation coefficient=0.22,P>0.05).●CONCLUSION:There is a high accuracy for the detection of glaucoma with AI with SD-OCT images.The application of AI-based algorithms allows together with“doctor+artificial intelligence”to improve the diagnosis of glaucoma.展开更多
文摘Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone disease.Methods:A comprehensive literature review was performed using PubMed,Scopus,and Google Scholar databases to identify publications about innovative concepts or supporting applications of AI in the improvement of every medical procedure relating to stone disease.The terms“endourology”,“artificial intelligence”,“machine learning”,and“urolithiasis”were used for searching eligible reports,while review articles,articles referring to automated procedures without AI application,and editorial comments were excluded from the final set of publications.The search was conducted from January 2000 to September 2023 and included manuscripts in the English language.Results: A total of 69 studies were identified.The main subjects were related to the detection of urinary stones,the prediction of the outcome of conservative or operative management,the optimization of operative procedures,and the elucidation of the relation of urinary stone chemistry with various factors.Conclusion: AI represents a useful tool that provides urologists with numerous amenities,which explains the fact that it has gained ground in the pursuit of stone disease management perfection.The effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing data.However,little is known concerning the potential of this vast field.Electronic patient records,containing big data,offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms.Nevertheless,the existing applications are not generalizable in real-life practice,and high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.
文摘Objective:To evaluate the feasibility and the safety of medial non-papillary percutaneous nephrolithotomy(npPCNL)for the management of large proximal ureteral stones.Methods:We evaluated prospectively collected data of 37 patients with large proximal ureteral stones more than 1.5 cm in diameter treated by prone npPCNL.Depending on stone size,in-toto stone removal or lithotripsy using the Lithoclast®Trilogy(EMS Medical,Nyon,Switzerland)was performed.Perioperative parameters including operative time(from start of puncture to the skin suturing),stone extraction time(from the first insertion of the nephroscope to the extraction of all stone fragments),and the stone-free rate were evaluated.Results:Twenty-one males and 16 females underwent npPCNL for the management of large upper ureteral calculi.The median age and stone size of treated patients were 58(interquartile range[IQR]:51-69)years and 19.3(IQR:18.0-22.0)mm,respectively.The median operative time and stone extraction time were 25(IQR:21-29)min and 8(IQR:7-10)min,respectively.One case(2.7%)of postoperative bleeding and two cases(5.4%)of prolonged fever were managed conservatively.The stone-free rate at a 1-month follow-up was 94.6%.Conclusion:The npPCNL provides a straight route to the ureteropelvic junction and proximal ureter.Approaching from a dilated portion of the ureter under low irrigation pressure with larger diameter instruments results in effective and safe stone extraction within a few minutes.
文摘BACKGROUND Several studies have explored the long-term prognosis of patients with asymp-tomatic gallbladder stones.These reports were primarily conducted in facilities equipped with beds for addressing symptomatic cases.AIM To report the long-term prognosis of patients with asymptomatic gallbladder stones in clinics without bed facilities.METHODS We investigated the prognoses of 237 patients diagnosed with asymptomatic gallbladder stones in clinics without beds between March 2010 and October 2022.When symptoms developed,patients were transferred to hospitals where appropriate treatment was possible.We investigated the asymptomatic and survival periods during the follow-up.RESULTS Among the 237 patients,214(90.3%)remained asymptomatic,with a mean asymptomatic period of 3898.9279±46.871 d(50-4111 d,10.7 years on average).Biliary complications developed in 23 patients(9.7%),with a mean survival period of 4010.0285±31.2788 d(53-4112 d,10.9 years on average).No patient died of biliary complications.CONCLUSION The long-term prognosis of asymptomatic gallbladder stones in clinics without beds was favorable.When the condition became symptomatic,the patients were transferred to hospitals with beds that could address it;thus,no deaths related to biliary complications were reported.This finding suggests that follow-up care in clinics without beds is possible.
文摘Hepatolithiasis(HL)poses a significant risk for cholangiocarcinoma(CCA)development,with reported incidences ranging from 5%-13%.Risk factors include older age,smoking,hepatitis B infection,and prolonged HL duration.Chronic inflammation and mechanical stress on the biliary epithelium contribute to CCA pathogenesis.Hepatectomy reduces CCA risk by removing stones and atrophic liver segments.However,residual stones and incomplete removal increase CCA risk.Kim et al identified carbohydrate antigen 19-9,carcinoembryonic antigen,and stone laterality as CCA risk factors,reaffirming the importance of complete stone removal.Nonetheless,challenges remain in preventing CCA recurrence post-surgery.Longer-term studies are needed to elucidate CCA risk factors further.
文摘Artificial intelligence(AI)is making significant strides in revolutionizing the detection of Barrett's esophagus(BE),a precursor to esophageal adenocarcinoma.In the research article by Tsai et al,researchers utilized endoscopic images to train an AI model,challenging the traditional distinction between endoscopic and histological BE.This approach yielded remarkable results,with the AI system achieving an accuracy of 94.37%,sensitivity of 94.29%,and specificity of 94.44%.The study's extensive dataset enhances the AI model's practicality,offering valuable support to endoscopists by minimizing unnecessary biopsies.However,questions about the applicability to different endoscopic systems remain.The study underscores the potential of AI in BE detection while highlighting the need for further research to assess its adaptability to diverse clinical settings.
基金supported by the National Natural Science Foundation of China(Grant Nos.21908052 and 22108200)the Key Program of the Natural Science Foundation of Hebei Province(Grant No.B2020209017)+2 种基金the Project of Science and Technology Innovation Team,Tangshan(Grant No.20130203D)the Natural Science Foundation of Zhejiang Province(Grant No.LQ22B060013)and the Science and Technology Project of Hebei Education Department(Grant No.QN2021113).
文摘The artificial photosynthesis technology has been recognized as a promising solution for CO_(2) utilization.Photothermal catalysis has been proposed as a novel strategy to promote the efficiency of artificial photosynthesis by coupling both photochemistry and thermochemistry.However,strategies for maximizing the use of solar spectra with different frequencies in photothermal catalysis are urgently needed.Here,a hierarchical full-spectrum solar light utilization strategy is proposed.Based on this strategy,a Cu@hollow titanium silicalite-1 zeolite(TS-1)nanoreactor with spatially separated photo/thermal catalytic sites is designed to realize high-efficiency photothermal catalytic artificial photosynthesis.The space-time yield of alcohol products over the optimal catalyst reached 64.4μmol g−1 h−1,with the selectivity of CH3CH2OH of 69.5%.This rationally designed hierarchical utilization strategy for solar light can be summarized as follows:(1)high-energy ultraviolet light is utilized to drive the initial and difficult CO_(2) activation step on the TS-1 shell;(2)visible light can induce the localized surface plasmon resonance effect on plasmonic Cu to generate hot electrons for H2O dissociation and subsequent reaction steps;and(3)low-energy near-infrared light is converted into heat by the simulated greenhouse effect by cavities to accelerate the carrier dynamics.This work provides some scientific and experimental bases for research on novel,highly efficient photothermal catalysts for artificial photosynthesis.
基金supported by the Capital’s Funds for Health Improvement and Research,No.2022-2-2072(to YG).
文摘Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.
基金financed by the Jiangsu Haizhou Bay National Sea Ranching Demonstration Project(No.D-8005-18-0188)the Shanghai Municipal Science and Technology Commission Local Capacity Construction Project(No.21010502200).
文摘Plankton are an important component of marine protected areas(MPAs),and its communities would require much smaller interpatch distances to ensure connection among MPAs.According to the survey from MPAs dominated by artificial reefs and adjacent waters(estuary area(EA),aquaculture area(AA),artificial reef area(ARA),natural area(NA)and comprehensive effect area(CEA))in Haizhou Bay in spring and autumn,we analyzed phyto-zooplankton composition,abundance and biomass,and correlation with hydrologic variables to gain information about the forces that structure the plankton.The results showed that the dominant zooplankton were copepods(spring,98.9%;autumn,94.2%),while the phytoplankton were mainly composed of Bacillariophyta(spring,61.8%;autumn,95.6%).The RDA results showed that temperature,salinity and depth highly associated with the distribution and composition of plankton species among the habitats than other factors in spring;temperature,Chla and DO had the strongest influence in autumn.The zooplankton in the ARA and AA ecosystems basically contained the same species as those in other habitats,and each habitat also exhibited a relatively unique combination of plankton species.The structures of the EA zooplankton in spring and the EA phytoplankton in both seasons were much different than other habitats,which may have been caused by factors such as currents and tides.We concluded that there exists similarity of the plankton community between artificial reef area and adjacent waters,whereas the EAs may be relatively independent systems.Therefore,these interaction between plankton community should be considered when designing MPA networks,and ocean circulations should be considered more than the environmental factors.
基金financially supported by the National Natural Science Foundation of China, China (Nos. 52274252 and 51874047)the Special Fund for the Construction of Innovative Provinces in Hunan Province, China (No. 2020RC3038)the Changsha City Fund for Distinguished and Innovative Young Scholars, China (No. kq1802007)。
文摘Phase change materials (PCMs) can be incorporated with low-cost minerals to synthesize composites for thermal energy storage in building applications.Stone coal (SC) after vanadium extraction treatment shows potential for secondary utilization in composite preparation.We prepared SC-based composite PCMs with SC as a matrix,stearic acid (SA) as a PCM,and expanded graphite (EG) as an additive.The combined roasting and acid leaching treatment of raw SC was conducted to understand the effect of vanadium extraction on promoting loading capacity.Results showed that the combined treatment of roasting at 900℃ and leaching increased the SC loading of the composite by 6.2%by improving the specific surface area.The loading capacity and thermal conductivity of the composite obviously increased by 127%and 48.19%,respectively,due to the contribution of 3wt% EG.These data were supported by the high load of 66.69%and thermal conductivity of 0.59 W·m^(-1)·K-1of the designed composite.The obtained composite exhibited a phase change temperature of 52.17℃,melting latent heat of 121.5 J·g^(-1),and good chemical compatibility.The SC-based composite has prospects in building applications exploiting the secondary utilization of minerals.
文摘Background: The growth and use of Artificial Intelligence (AI) in the medical field is rapidly rising. AI is exhibiting a practical tool in the healthcare industry in patient care. The objective of this current review is to assess and analyze the use of AI and its use in orthopedic practice, as well as its applications, limitations, and pitfalls. Methods: A review of all relevant databases such as EMBASE, Cochrane Database of Systematic Reviews, MEDLINE, Science Citation Index, Scopus, and Web of Science with keywords of AI, orthopedic surgery, applications, and drawbacks. All related articles on AI and orthopaedic practice were reviewed. A total of 3210 articles were included in the review. Results: The data from 351 studies were analyzed where in orthopedic surgery. AI is being used for diagnostic procedures, radiological diagnosis, models of clinical care, and utilization of hospital and bed resources. AI has also taken a chunk of share in assisted robotic orthopaedic surgery. Conclusions: AI has now become part of the orthopedic practice and will further increase its stake in the healthcare industry. Nonetheless, clinicians should remain aware of AI’s serious limitations and pitfalls and consider the drawbacks and errors in its use.
基金Guangdong Basic and Applied Basic Research Foundation(No.2019B1515120011)Medical Research,Foshan Health and Wellness Department(No.20220374).
文摘AIM:To assess the efficacy of artificial natural light in preventing incident myopia in primary school-age children.METHODS:This is a prospective,randomized control,intervention study.A total of 1840 students from 39 classes in 4 primary schools in Foshan participated in this study.The whole randomization method was adopted to include classes as a group according to 1:1 randomized control.Classrooms in the control group were illuminated by usual light,and classrooms in the intervention group were illuminated by artificial natural light.All students received uncorrected visual acuity and best-corrected visual acuity measurement,non-cycloplegic autorefraction,ocular biometric examination,slit lamp and strabismus examination.Three-year follow-up,the students underwent same procedures.Myopia was defined as spherical equivalent refraction≤-0.50 D and uncorrected visual acuity<20/20.RESULTS:There were 894 students in the control group and 946 students in the intervention group with a mean±SD age of 7.50±0.53y.The three-year cumulative incidence rate of myopia was 26.4%(207 incident cases among 784 eligible participants at baseline)in the control group and 21.2%(164 incident cases among 774 eligible participants at baseline)in the intervention group[difference of 5.2%(95%CI,3.7%to 10.1%);P=0.035].There was also a significant difference in the three-year change in spherical equivalent refraction for the control group(-0.81 D)compared with the intervention group[-0.63 D;difference of 0.18 D(95%CI,0.08 to 0.28 D);P<0.001].Elongation of axial length was significantly different between in the control group(0.77 mm)and the intervention group[0.72 mm;difference of 0.05 mm(95%CI,0.01 to 0.09 mm);P=0.003].CONCLUSION:Artificial natural light in the classroom of primary schools can result in reducing incidence rate of myopia during a period of three years.
基金supported by grants from the Earmarked Fund for Agriculture Seed Improvement Project of Shandong Province(Nos.2021ZLGX03 and 2022LZGCQY010)the China Agriculture Research System Project(No.CARS-49).
文摘Pacific oyster(Crassostrea gigas)is one of the most important mollusks cultured all around the world.Selective breeding programs of Pacific oysters in China is initiated since 2006 and developed the genetically improved strain with fast-growing trait.However,little is known about the metabolic signatures of the fast-growing trait.In the present study,the non-targeted metabolomics was performed to analyze the metabolic signatures of adductor muscle tissue in one-year old Pacific oysters from fast-growing strain and the wild population.A total of 7767 and 10174 valid peaks were extracted and quantified in ESI^(+)and ESI^(−)modes,resulting in 399 and 381 annotated metabolites,respectively.PCA and OPLS-DA revealed that considerable separation among samples from fastgrowing strain and wild population,suggesting the differences in metabolic signatures.Meanwhile,81 significantly different metabolites(SDMs)were identified in the comparisons between fast-growing strain and wild population,based on the strict thresholds.It was found that there were highly correlation and conserved coordination among these SDMs.KEGG enrichment analysis indicated that the SDMs were tightly related to pantothenate and CoA biosynthesis,steroid hormone biosynthesis,riboflavin metabolism,and arginine and proline metabolism.Of them,the CoA biosynthesis and metabolism,affected by pantetheine and pantothenic acid,might be important for the growth of Pacific oysters under artificial selective breeding.The study provides the comprehensive views of metabolic signatures in response to artificially selective breeding,and is helpful to better understand the molecular mechanism of fastgrowing traits in Pacific oysters.
文摘The research investigated the adoption of artificial intelligence (AI) technol-ogies among agricultural entrepreneurs in Ondo state, Nigeria. A purposive sample of 120 participants involved in agriculture was selected for the study. Socioeconomic characteristics analysis revealed that the mean age of the re-spondents was 48.3 years. A majority (77%) of the respondents were male, and approximately 68% were married. Regarding education, 32.5% had completed secondary education, while 32.5% had tertiary education. The av-erage annual income was 1,166,800 naira, with a significant proportion (71.7%) identifying as Christians. The study found a significant association between respondents’ awareness levels and their adoption of AI-enabled technologies (χ<sup>2</sup> = 7.714, p = 0.005). Based on these findings, it is recom-mended that extension officers receive training in the latest agricultural technologies, including those enabled by AI. Furthermore, the study suggests the introduction of easily accessible and user-friendly AI technologies to farmers to enhance their productivity and income with minimal or no cost implications.
文摘Global health (GH) aims to improve healthcare for all people on the planet and eradicate all avoidable diseases and deaths. The inception of Artificial Intelligence (AI) is innovating healthcare practices and improving patient outcomes by shuffling enormous volumes of health data—from health records and clinical studies to genetic information analyzing it much faster than humans. AI also helps in the improvement of medical imaging and medical diagnosis. There is an increased optimism regarding the use of applications of AI locally but can these facets be translated globally in the advancement and delivery of healthcare with the help of AI. At present majority of AI developments and applications in health care provide to the needs of developed countries and there is little effort to develop programs which could help to improve healthcare delivery globally. We performed this narrative review to assess the difficulties and discrepancies in implementing AI in global health delivery and find ways to improve.
文摘Objective: To explore the application value of rapid rehabilitation concept in patients with extrahepatic bile duct stones under laparoscopy during perioperative period. Methods: 90 patients with extrahepatic bile duct stones treated in our hospital from January 2022 to February 2023 were selected as the research object and randomly divided into the study group and the control group. The control group was given routine care, and the observation group was given rapid surgical rehabilitation care. The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time, hospitalization time and complication rate were compared between the two groups. The independent sample T test was used for the measurement data, and the x<sup>2</sup> test was used for the counting data, and the difference was statistically significant (P Results: The postoperative anal exhaust time, first meal time, early activity time, pain time, abdominal drainage tube removal time and hospitalization time in the study group were shorter than those in the control group (all P Conclusion: The concept of rapid rehabilitation can significantly improve the perioperative nursing effect of patients with extrahepatic bile duct stones and accelerate their rehabilitation, which is worth improving and popularizing.
文摘In this editorial we comment on the article“Potential and limitations of ChatGPT and generative artificial intelligence in medial safety education”published in the recent issue of the World Journal of Clinical Cases.This article described the usefulness of artificial intelligence(AI)in medial safety education.Herein,we focus specifically on the use of AI in the field of pain medicine.AI technology has emerged as a powerful tool,and is expected to play an important role in the healthcare sector and significantly contribute to pain medicine as further developments are made.AI may have several applications in pain medicine.First,AI can assist in selecting testing methods to identify causes of pain and improve diagnostic accuracy.Entry of a patient’s symptoms into the algorithm can prompt it to suggest necessary tests and possible diagnoses.Based on the latest medical information and recent research results,AI can support doctors in making accurate diagnoses and setting up an effective treatment plan.Second,AI assists in interpreting medical images.For neural and musculoskeletal disorders,imaging tests are of vital importance.AI can analyze a variety of imaging data,including that from radiography,computed tomography,and magnetic resonance imaging,to identify specific patterns,allowing quick and accurate image interpretation.Third,AI can predict the outcomes of pain treatments,contributing to setting up the optimal treatment plan.By predicting individual patient responses to treatment,AI algorithms can assist doctors in establishing a treatment plan tailored to each patient,further enhancing treatment effectiveness.For efficient utilization of AI in the pain medicine field,it is crucial to enhance the accuracy of AI decision-making by using more medical data,while issues related to the protection of patient personal information and responsibility for AI decisions will have to be addressed.In the future,AI technology is expected to be innovatively applied in the field of pain medicine.The advancement of AI is anticipated to have a positive impact on the entire medical field by providing patients with accurate and effective medical services.
文摘Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce. Aim: To test a novel AI commercially available tool for image analysis on a series of laparoscopic scenes. Methods: The research tools included OPENAI CHATGPT 4.0 with its corresponding image recognition plugin which was fed with a list of 100 laparoscopic selected snapshots from common surgical procedures. In order to score reliability of received responses from image-recognition bot, two corresponding scales were developed ranging from 0 - 5. The set of images was divided into two groups: unlabeled (Group A) and labeled (Group B), and according to the type of surgical procedure or image resolution. Results: AI was able to recognize correctly the context of surgical-related images in 97% of its reports. For the labeled surgical pictures, the image-processing bot scored 3.95/5 (79%), whilst for the unlabeled, it scored 2.905/5 (58.1%). Phases of the procedure were commented in detail, after all successful interpretations. With rates 4 - 5/5, the chatbot was able to talk in detail about the indications, contraindications, stages, instrumentation, complications and outcome rates of the operation discussed. Conclusion: Interaction between surgeon and chatbot appears to be an interesting frontend for further research by clinicians in parallel with evolution of its complex underlying infrastructure. In this early phase of using artificial intelligence for image recognition in surgery, no safe conclusions can be drawn by small cohorts with commercially available software. Further development of medically-oriented AI software and clinical world awareness are expected to bring fruitful information on the topic in the years to come.
文摘Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based algorithms.In this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and decision-making.Federated Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data effectively.In this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare systems.The experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)platform.The experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.
文摘●AIM:To quantify the performance of artificial intelligence(AI)in detecting glaucoma with spectral-domain optical coherence tomography(SD-OCT)images.●METHODS:Electronic databases including PubMed,Embase,Scopus,ScienceDirect,ProQuest and Cochrane Library were searched before May 31,2023 which adopted AI for glaucoma detection with SD-OCT images.All pieces of the literature were screened and extracted by two investigators.Meta-analysis,Meta-regression,subgroup,and publication of bias were conducted by Stata16.0.The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool.●RESULTS:Twenty studies and 51 models were selected for systematic review and Meta-analysis.The pooled sensitivity and specificity were 0.91(95%CI:0.86–0.94,I2=94.67%),0.90(95%CI:0.87–0.92,I2=89.24%).The pooled positive likelihood ratio(PLR)and negative likelihood ratio(NLR)were 8.79(95%CI:6.93–11.15,I2=89.31%)and 0.11(95%CI:0.07–0.16,I2=95.25%).The pooled diagnostic odds ratio(DOR)and area under curve(AUC)were 83.58(95%CI:47.15–148.15,I2=100%)and 0.95(95%CI:0.93–0.97).There was no threshold effect(Spearman correlation coefficient=0.22,P>0.05).●CONCLUSION:There is a high accuracy for the detection of glaucoma with AI with SD-OCT images.The application of AI-based algorithms allows together with“doctor+artificial intelligence”to improve the diagnosis of glaucoma.
