Background:Traditional Chinese medicine(TCM)is commonly used for the diagnosis and treatment of insomnia,with tongue diagnosis being particularly important.The aim of our study was to develop and validate a novel tong...Background:Traditional Chinese medicine(TCM)is commonly used for the diagnosis and treatment of insomnia,with tongue diagnosis being particularly important.The aim of our study was to develop and validate a novel tongue imaging-based radiomics(TIR)method for accurately diagnosing insomnia severity.Methods:This two-center analysis prospectively enrolled 399 patients who underwent tongue imaging between July and October 2021 and divided them into primary and validation cohorts by study center.Here,we referred to the Insomnia Severity Index(ISI)standard and the degree of insomnia was evaluated as absent,subthreshold,moderate,or severe.For developed the TIR diagnostic tool,a U-Net algorithm was used to segment tongue images.Subsequently,seven imaging features were selected from the extracted high-throughout radiomics features using the least absolute shrinkage and selection operator algorithm.Then,the final radiomics model was developed in the primary cohort and tested in the independent validation cohort.Finally,we assessed and compared the diagnostic performance differences between TCM tongue diagnosis and our TIR diagnostic tool with the ISI gold standard.The confusion matrix was calculated to evaluate the diagnostic performance.Results:Seven tongue imaging features were selected to build the TIR tool,with showing good correlations with the insomnia degree.The TIR method had an accuracy of 0.798,a macro-average sensitivity of 0.78,a macro-average specificity of 0.906,a weighted-average sensitivity of 0.798,and a weighted specificity of 0.916,showing a significantly better performance compared to the average performance of three experienced TCM physicians(mean accuracy of 0.458,P<0.01).Conclusions:The preliminary study demonstrates the potential application of TIR in the diagnosis of insomnia degree and measurement of sleep health.The integration of quantitative imaging analysis and machine learning algorithms holds promise for advancing both of TCM and precision sleep medicine.展开更多
Squeezed light is a critical resource in quantum sensing and information processing. Due to the inherently weak optical nonlinearity and limited interaction volume, considerable pump power is typically needed to obtai...Squeezed light is a critical resource in quantum sensing and information processing. Due to the inherently weak optical nonlinearity and limited interaction volume, considerable pump power is typically needed to obtain efficient interactions to generate squeezed light in bulk crystals. Integrated photonics offers an elegant way to increase the nonlinearity by confining light strictly inside the waveguide. For the construction of large-scale quantum systems performing many-photon operations, it is essential to integrate various functional modules on a chip. However, fabrication imperfections and transmission cross talk may add unwanted diffraction and coupling to other photonic elements, reducing the quality of squeezing. Here, by introducing the topological phase, we experimentally demonstrate the topologically protected nonlinear process of four-wave mixing, enabling the generation of squeezed light on a silica chip. We measure the cross-correlations at different evolution distances for various topological sites and verify the nonclassical features with high fidelity. The squeezing parameters are measured to certify the protection of cavity-free, strongly squeezed states. The demonstration of topological protection for squeezed light on a chip brings new opportunities for quantum integrated photonics,opening novel approaches for the design of advanced multi-photon circuits.展开更多
基金supported by the Shandong Province Traditional Chinese Medicine Science and Technology Project (M-2022012)。
文摘Background:Traditional Chinese medicine(TCM)is commonly used for the diagnosis and treatment of insomnia,with tongue diagnosis being particularly important.The aim of our study was to develop and validate a novel tongue imaging-based radiomics(TIR)method for accurately diagnosing insomnia severity.Methods:This two-center analysis prospectively enrolled 399 patients who underwent tongue imaging between July and October 2021 and divided them into primary and validation cohorts by study center.Here,we referred to the Insomnia Severity Index(ISI)standard and the degree of insomnia was evaluated as absent,subthreshold,moderate,or severe.For developed the TIR diagnostic tool,a U-Net algorithm was used to segment tongue images.Subsequently,seven imaging features were selected from the extracted high-throughout radiomics features using the least absolute shrinkage and selection operator algorithm.Then,the final radiomics model was developed in the primary cohort and tested in the independent validation cohort.Finally,we assessed and compared the diagnostic performance differences between TCM tongue diagnosis and our TIR diagnostic tool with the ISI gold standard.The confusion matrix was calculated to evaluate the diagnostic performance.Results:Seven tongue imaging features were selected to build the TIR tool,with showing good correlations with the insomnia degree.The TIR method had an accuracy of 0.798,a macro-average sensitivity of 0.78,a macro-average specificity of 0.906,a weighted-average sensitivity of 0.798,and a weighted specificity of 0.916,showing a significantly better performance compared to the average performance of three experienced TCM physicians(mean accuracy of 0.458,P<0.01).Conclusions:The preliminary study demonstrates the potential application of TIR in the diagnosis of insomnia degree and measurement of sleep health.The integration of quantitative imaging analysis and machine learning algorithms holds promise for advancing both of TCM and precision sleep medicine.
基金National Key R&D Program of China(2019YFA0308700, 2019YFA0706302, 2017YFA0303700)National Natural Science Foundation of China (NSFC)(11904229, 61734005, 11761141014, 11690033)+4 种基金Science and Technology Commission of Shanghai Municipality (STCSM)(20JC1416300, 2019SHZDZX01)Shanghai Municipal Education Commission (SMEC)(2017-01-07-00-02-E00049)China Postdoctoral Science Foundation (2020M671091)Australian Research Council (DE180100070)University of Technology Sydney Seed Fund。
文摘Squeezed light is a critical resource in quantum sensing and information processing. Due to the inherently weak optical nonlinearity and limited interaction volume, considerable pump power is typically needed to obtain efficient interactions to generate squeezed light in bulk crystals. Integrated photonics offers an elegant way to increase the nonlinearity by confining light strictly inside the waveguide. For the construction of large-scale quantum systems performing many-photon operations, it is essential to integrate various functional modules on a chip. However, fabrication imperfections and transmission cross talk may add unwanted diffraction and coupling to other photonic elements, reducing the quality of squeezing. Here, by introducing the topological phase, we experimentally demonstrate the topologically protected nonlinear process of four-wave mixing, enabling the generation of squeezed light on a silica chip. We measure the cross-correlations at different evolution distances for various topological sites and verify the nonclassical features with high fidelity. The squeezing parameters are measured to certify the protection of cavity-free, strongly squeezed states. The demonstration of topological protection for squeezed light on a chip brings new opportunities for quantum integrated photonics,opening novel approaches for the design of advanced multi-photon circuits.
