摘要
肝病学已经发展成为一门新兴的独立学科,但是相关的临床教学发展却相对滞后,因此,探讨科学规范的教学模式已成为时代要求。在肝病科的临床教学中,与传统教学模式相比,人工智能技术的引入可以结合网络现有的海量临床数据,从定义、诱因、分类、诊疗、推荐意见等方面,从而对于肝脏疾病的基础和临床教学做深度阐述。人工智能还可基于指南所引用的参考文献,完善和整合肝病教学资源,建设典型病例教学资料库,弥补临床实践教学中典型病例不足的现状,对复杂疑难的肝脏疾病进行深度学习,从而提高肝病科医师的临床诊疗能力。为了让肝病科的医学教育工作者对人工智能的应用做好充分准备,文章分析人工智能在我国肝脏疾病科临床教学中应用前景及作用。
Hepatology has developed into a new independent subject,but the related clinical teaching development is relatively lagging behind.Therefore,it has become the requirement of the times to explore a scientific and standardized teaching model of hepatology.In the clinical teaching of liver diseases,compared to traditional teaching models,the introduction of artificial intelligence technology can combine the massive clinical data available on the network,from the aspects of definition,incentives,classification,diagnosis and treatment,recommendations,etc.,to provide in-depth explanations on the basic and clinical teaching of liver diseases.Artificial intelligence can also improve and integrate liver disease teaching resources based on the references cited in the guide,build a typical case teaching database,make up for the lack of typical cases in clinical practice teaching,and conduct in-depth learning on complex and difficult liver diseases,thereby improving the clinical diagnosis and treatment ability of treatment ability of hepatology doctors.In order to make the medical educators in the department of liver diseases fully prepare for the application of artificial intelligence,this paper analyzes the application prospect and role of artificial intelligence in the clinical teaching of the department of liver diseases in China.
作者
黄昂
邹正升
HUANG Ang;ZOU Zhengsheng(Department of Hepatology,Division of Hepatology,the Fifth Medical Center of PLA General Hospital,Beijing 100039,China)
出处
《中国继续医学教育》
2023年第11期141-145,共5页
China Continuing Medical Education
基金
国家自然科学基金资助项目(82070584)国家自然科学基金资助项目(81600453)
北京市科技专项资助项目(Z171100001117114)。
关键词
人工智能
肝病学
医学教育
教学方法
应用探讨
非感染性肝病
artificial intelligence
hepatology
medical education
teaching methods
application and investigation
non-infectious liver disease
