The classical latent structure method does not consider the influence of primary and secondary symptoms,syndromes and symptoms in the analysis and modeling of syndromes.In this paper,based on the data of damp-heat in intestine and stomach syndrome involving 1087 diabetic patients,the classical latent structure analysis was used to obtain the quantitative syndrome diagnostic rules.Then,using Constrained Latent Tree Analysis(CLTA),the quantitative syndrome diagnostic rules containing primary and secondary symptoms were obtained as follows,primary symptoms include halitosis(2.3),yellow tongue coating(2),abdominal distension(2.3),greasy tongue coating(2.1),loose stool or loose stool(1.5),red tongue(1.3),smooth pulse(1.4).Secondary symptoms include epigastric distension(1.1).Compared with the traditional latent structure analysis method,the rules established by CLTA are more compatible with the concept of differentiating primary and secondary symptoms and the common practice of TCM.The quantitative syndrome diagnostic rules of damp-heat in intestine and stomach syndrome constructed by the CLTA method have considerable objectivity in the modeling process.The diagnostic rules established were also compatible with the qualitative concept of TCM theory in stratifying primary and secondary symptoms.Finally,the diagnostic rules are obtained by logistic regression analysis,and the accuracy of the three rules is compared.The results show that the rule recognition accuracy obtained by CLTA is the highest.Therefore,the syndrome diagnostic rules of damp-heat in intestine and stomach obtained from the analysis of CLTA are in line with the constraint semantics of primary and secondary diseases and the theory of traditional Chinese medicine.

Objective To investigate the epidemiological aspects of traditional Chinese medicine(TCM)deficiency,excess syndromes and physical characteristics related to insomnia in China from 2000 to 2023.Methods A search was conducted across CNKI,WANFANG DATA,VIP,and PubMed databases to identify epidemiological studies on the deficiency-excess syndrome differentiation in TCM and TCM body constitution distribution among Chinese patients with insomnia.Descriptive statistical analysis was performed to summarize the syndrome differentiation patterns,geographical distribution,and demographic characteristics of the study populations.Results A total of 44 relevant studies were included,encompassing 22184 insomnia patients from 23 provinces,municipalities,and autonomous regions.Among these studies,75.0%employed cross-sectional research methods,while the remainder utilized retrospective analysis(6.8%),cohort studies(2.3%),and 15.9%did not specify their research methods.The primary focus of the surveys revealed that 52.3%concentrated on the distribution of syndromes,31.8%on the distribution of body constitution,and 38.6%on the distribution of primary symptoms of insomnia.The main survey results indicated that the majority of insomnia patients in China exhibited excess syndrome,accounting for 61.7%,while deficiency syndrome comprised 38.3%.The main findings indicated that the predominant TCM syndrome among insomnia patients in China was Qi deficiency of the heart and spleen,accounting for 54.6%.In the empirical population,Qi stagnation transforming into fire constituted 46.3%.Conclusion Over the past two decades,substantial data has been accumulated in China on the deficiency-excess syndrome differentiation and body constitution distribution in TCM for insomnia,providing a foundational basis for future research in this field.

Objective To construct a self-service traditional Chinese medicine(TCM)syndrome differentiation-based home sleep scenario and establish a home-based TCM sleep aid environment.Methods Based on medical principles and modern sleep-related technologies,this study divided the home sleep scenario into four dimensions:Perception,syndrome differentiation,intervention,and evaluation.It proposed a construction plan for a self-service TCM sleep aid home scenario that integrated these four dimensions.Results The proposed TCM sleep aid scenario solution enables collaborative collection data from various devices in a home setting.This involved the setup of hardware at the perception level,the development of software at the syndrome differentiation level,the integration of hardware at the intervention level,and data cleaning,fusion,and analysis at the evaluation level.These four components are interconnected,allowing for the extraction of physiological data that is valuable for TCM-based population classification and intervention,which can be used to update algorithms and improve accuracy through iterative upgrades.Conclusion The construction of a home sleep scenario based on TCM syndrome differentiation is feasible and can provide a reference for the promotion and application of appropriate TCM techniques in home settings.

By analyzing the problems existing in the existing medical service model,this paper explores the core health needs of people in the era of intelligent medical care,and puts forward people-oriented,"4S-PAMA"(Self-Perception,Self-Assessment,Self-Management,Self-Adaption)health service model with individual active health promotion as the core.At the same time to build a multi-level,many modules,interactive health management of traditional Chinese medicine harbor as the breakthrough point,science and technology innovation as the means,through to transform traditional medical center or create new health management,in order to further carry out"perception model of the health management"model applied to provide theoretical basis.

Objective To investigate the epidemiological aspects of traditional Chinese medicine(TCM)deficiency,excess syndromes and physical characteristics related to insomnia in China from 2000 to 2023.Methods A search was conducted across CNKI,WANFANG DATA,VIP,and PubMed databases to identify epidemiological studies on the deficiency-excess syndrome differentiation in TCM and TCM body constitution distribution among Chinese patients with insomnia.Descriptive statistical analysis was performed to summarize the syndrome differentiation patterns,geographical distribution,and demographic characteristics of the study populations.Results A total of 44 relevant studies were included,encompassing 22184 insomnia patients from 23 provinces,municipalities,and autonomous regions.Among these studies,75.0%employed cross-sectional research methods,while the remainder utilized retrospective analysis(6.8%),cohort studies(2.3%),and 15.9%did not specify their research methods.The primary focus of the surveys revealed that 52.3%concentrated on the distribution of syndromes,31.8%on the distribution of body constitution,and 38.6%on the distribution of primary symptoms of insomnia.The main survey results indicated that the majority of insomnia patients in China exhibited excess syndrome,accounting for 61.7%,while deficiency syndrome comprised 38.3%.The main findings indicated that the predominant TCM syndrome among insomnia patients in China was Qi deficiency of the heart and spleen,accounting for 54.6%.In the empirical population,Qi stagnation transforming into fire constituted 46.3%.Conclusion Over the past two decades,substantial data has been accumulated in China on the deficiency-excess syndrome differentiation and body constitution distribution in TCM for insomnia,providing a foundational basis for future research in this field.

The classical latent structure method does not consider the influence of primary and secondary symptoms,syndromes and symptoms in the analysis and modeling of syndromes.In this paper,based on the data of damp-heat in intestine and stomach syndrome involving 1087 diabetic patients,the classical latent structure analysis was used to obtain the quantitative syndrome diagnostic rules.Then,using Constrained Latent Tree Analysis(CLTA),the quantitative syndrome diagnostic rules containing primary and secondary symptoms were obtained as follows,primary symptoms include halitosis(2.3),yellow tongue coating(2),abdominal distension(2.3),greasy tongue coating(2.1),loose stool or loose stool(1.5),red tongue(1.3),smooth pulse(1.4).Secondary symptoms include epigastric distension(1.1).Compared with the traditional latent structure analysis method,the rules established by CLTA are more compatible with the concept of differentiating primary and secondary symptoms and the common practice of TCM.The quantitative syndrome diagnostic rules of damp-heat in intestine and stomach syndrome constructed by the CLTA method have considerable objectivity in the modeling process.The diagnostic rules established were also compatible with the qualitative concept of TCM theory in stratifying primary and secondary symptoms.Finally,the diagnostic rules are obtained by logistic regression analysis,and the accuracy of the three rules is compared.The results show that the rule recognition accuracy obtained by CLTA is the highest.Therefore,the syndrome diagnostic rules of damp-heat in intestine and stomach obtained from the analysis of CLTA are in line with the constraint semantics of primary and secondary diseases and the theory of traditional Chinese medicine.

By analyzing the problems existing in the existing medical service model,this paper explores the core health needs of people in the era of intelligent medical care,and puts forward people-oriented,"4S-PAMA"(Self-Perception,Self-Assessment,Self-Management,Self-Adaption)health service model with individual active health promotion as the core.At the same time to build a multi-level,many modules,interactive health management of traditional Chinese medicine harbor as the breakthrough point,science and technology innovation as the means,through to transform traditional medical center or create new health management,in order to further carry out"perception model of the health management"model applied to provide theoretical basis.

With the scientific and modernization of acupuncture,various kinds of acupuncture medical equipment continue to innovate,especially with the emergence of intelligent acupuncture diagnosis and treatment units,automatic detection of acupuncture needles in the"needle retention"stage of acupuncture clinical practice has become a hot demand.Aiming at the problems that the input image size is too large,the acupuncture needles are slender,and the acupuncture needles are densely distributed,the Acupuncture Needle Object Detection Model(ANODM),an improved YOLOv5 model for acupuncture needles,is proposed in this paper.① In the preprocessing stage,the image is divided into multiple patches for prediction,respectively.② At the model structure level,a new small object detection layer is added to the original three detection layers to improve the recognition ability of small objects.The ordinary convolution of the backbone network is replaced by the dialated convolution to increase the sensitivity field.Features of different stages are fused.③ In the post-processing stage,Soft-NMS is used to reduce the miss rate of positive samples,and cosine similarity match is used to reduce the error rate of negative samples.The experimental results show that,compared with the original YOLOv5,the detection accuracy of the improved YOLOv5 in this paper is improved by 4.2%on the acupuncture needle small object dataset,which can better complete the acupuncture needle small target detection task.

Objective To construct a self-service traditional Chinese medicine(TCM)syndrome differentiation-based home sleep scenario and establish a home-based TCM sleep aid environment.Methods Based on medical principles and modern sleep-related technologies,this study divided the home sleep scenario into four dimensions:Perception,syndrome differentiation,intervention,and evaluation.It proposed a construction plan for a self-service TCM sleep aid home scenario that integrated these four dimensions.Results The proposed TCM sleep aid scenario solution enables collaborative collection data from various devices in a home setting.This involved the setup of hardware at the perception level,the development of software at the syndrome differentiation level,the integration of hardware at the intervention level,and data cleaning,fusion,and analysis at the evaluation level.These four components are interconnected,allowing for the extraction of physiological data that is valuable for TCM-based population classification and intervention,which can be used to update algorithms and improve accuracy through iterative upgrades.Conclusion The construction of a home sleep scenario based on TCM syndrome differentiation is feasible and can provide a reference for the promotion and application of appropriate TCM techniques in home settings.

With the scientific and modernization of acupuncture,various kinds of acupuncture medical equipment continue to innovate,especially with the emergence of intelligent acupuncture diagnosis and treatment units,automatic detection of acupuncture needles in the"needle retention"stage of acupuncture clinical practice has become a hot demand.Aiming at the problems that the input image size is too large,the acupuncture needles are slender,and the acupuncture needles are densely distributed,the Acupuncture Needle Object Detection Model(ANODM),an improved YOLOv5 model for acupuncture needles,is proposed in this paper.① In the preprocessing stage,the image is divided into multiple patches for prediction,respectively.② At the model structure level,a new small object detection layer is added to the original three detection layers to improve the recognition ability of small objects.The ordinary convolution of the backbone network is replaced by the dialated convolution to increase the sensitivity field.Features of different stages are fused.③ In the post-processing stage,Soft-NMS is used to reduce the miss rate of positive samples,and cosine similarity match is used to reduce the error rate of negative samples.The experimental results show that,compared with the original YOLOv5,the detection accuracy of the improved YOLOv5 in this paper is improved by 4.2%on the acupuncture needle small object dataset,which can better complete the acupuncture needle small target detection task.