Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.006
Ran Li , Gao Ren , Junfeng Yan , Beiji Zou , Qingping Liu
Objective
To construct a traditional Chinese medicine (TCM) knowledge base using knowledge graph based on deep learning methods, and to explore the application of joint models in intelligent question answering systems for TCM.
Methods
Textbooks Prescriptions of Chinese Materia Medica and Chinese Materia Medica were applied to construct a comprehensive knowledge graph serving as the foundation for the intelligent question answering system. In the study, a BERT+Slot-Gated (BSG) deep learning model was applied for the identification of TCM entities and question intentions presented by users in their questions. Answers retrieved from the knowledge graph based on the identified entities and intentions were then returned to the user. The Flask framework and BSG model were utilized to develop the intelligent question answering system of TCM.
Results
A TCM knowledge map encompassing 3 149 entities and 6 891 relational triples based on the prescriptions and Chinese materia medica was drawn. In the question answering test assisted by a question corpus, the F1 value for recognizing entities when answering 20 types of TCM questions was 0.996 9, and the accuracy rate for identifying intentions was 99.75%. This indicates that the system is both feasible and practical. Users can interact with the system through the WeChat Official Account platform.
Conclusion
The BSG model proposed in this paper achieved good results in experiments by increasing the vector dimension, indicating the effectiveness of the joint model method and providing new research ideas for the implementation of intelligent question answering systems in TCM.
{"title":"Intelligent question answering system for traditional Chinese medicine based on BSG deep learning model: taking prescription and Chinese materia medica as examples","authors":"Ran Li , Gao Ren , Junfeng Yan , Beiji Zou , Qingping Liu","doi":"10.1016/j.dcmed.2024.04.006","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.006","url":null,"abstract":"<div><h3>Objective</h3><p>To construct a traditional Chinese medicine (TCM) knowledge base using knowledge graph based on deep learning methods, and to explore the application of joint models in intelligent question answering systems for TCM.</p></div><div><h3>Methods</h3><p>Textbooks <em>Prescriptions of Chinese Materia Medica</em> and <em>Chinese Materia Medica</em> were applied to construct a comprehensive knowledge graph serving as the foundation for the intelligent question answering system. In the study, a BERT+Slot-Gated (BSG) deep learning model was applied for the identification of TCM entities and question intentions presented by users in their questions. Answers retrieved from the knowledge graph based on the identified entities and intentions were then returned to the user. The Flask framework and BSG model were utilized to develop the intelligent question answering system of TCM.</p></div><div><h3>Results</h3><p>A TCM knowledge map encompassing 3 149 entities and 6 891 relational triples based on the prescriptions and Chinese materia medica was drawn. In the question answering test assisted by a question corpus, the F1 value for recognizing entities when answering 20 types of TCM questions was 0.996 9, and the accuracy rate for identifying intentions was 99.75%. This indicates that the system is both feasible and practical. Users can interact with the system through the WeChat Official Account platform.</p></div><div><h3>Conclusion</h3><p>The BSG model proposed in this paper achieved good results in experiments by increasing the vector dimension, indicating the effectiveness of the joint model method and providing new research ideas for the implementation of intelligent question answering systems in TCM.</p></div>","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000247/pdfft?md5=a22431df2b6bfa13b9ef1cab13e2e4d5&pid=1-s2.0-S2589377724000247-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the theories of pulse disgnosis in traditional Chinese medicine (TCM), it is emphasized that pulse manifestations at the radial artery within the wrist (called Cunkou) signify the physiological and pathological conditions of different internal organs in the human body. However, different opinions exist among researchers about the objectiveness of the pulse diagnosis technique. Some researchers mentioned that no significant differences were observed in pulse manifestations at various Cunkou areas, hence there might be some difficulty in evaluating the status of different organs through checking pulse manifestations at Cunkou. This research aims to analyze the pulse response at Cunkou from the aspect of the characteristics of tactile sensing, thus to give a preliminary explanation to the above question.
Methods
This research utilized the Weber-Fechner law to model the tactile sensing as a dynamic low-pass signal filter with varying bandwidths under different compression levels during pulse diagnosis. The model was applied to analyzing the clinical data collected previously by our group. The arterial pressures measured invasively with equipment from 14 patients with aorta coarctation were processed to simulate different pulse manifestations at Cun, Guan, and Chi positions of Cunkou when different compression levels were applied.
Results
Due to the characteristics of tactile sensing, significant variations were observed in pulse manifestations at different pulse-depths under the application of changing compression levels; while no such changes in pulse manifestations were observed from the employment of transducer only, without tactile sensing involved. The results explained why different understandings on pulse manifestations were formed between direct pulse-taking technique in TCM and modern sphygmography using transducers. The features of pulse manifestations at Cunkou, using direct pulse-taking technique but at different depths, superficial, middle, and deep positions, respectively, predicted by the developed tactile sensing model were in line with those described in TCM pulse theories.
Conclusion
Based on the developed tactile sensing model, this study preliminarily explains the phenomenon that pulse manifestation at Cunkou changes in response to the compression force applied during TCM pulse-taking. Integrating the tactile sensing model with the study of TCM pulse diagnosis opens a new chapter for visualizing and quantitatively interpreting pulse manifestations. This not only expands the scope of pulse diagnosis study effectively, but also provide a scientific basis for further technical upgrading and optimization of existing pulse diagnosis equipment.
{"title":"Differences in pulse manifestations at Cunkou based on simplified modeling of tactile sensing","authors":"S.H.I. Yubing , Y.A.N.G. Hongyi , Y.E.O. Joon Hock","doi":"10.1016/j.dcmed.2024.04.004","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.004","url":null,"abstract":"<div><h3>Objective</h3><p>In the theories of pulse disgnosis in traditional Chinese medicine (TCM), it is emphasized that pulse manifestations at the radial artery within the wrist (called Cunkou) signify the physiological and pathological conditions of different internal organs in the human body. However, different opinions exist among researchers about the objectiveness of the pulse diagnosis technique. Some researchers mentioned that no significant differences were observed in pulse manifestations at various Cunkou areas, hence there might be some difficulty in evaluating the status of different organs through checking pulse manifestations at Cunkou. This research aims to analyze the pulse response at Cunkou from the aspect of the characteristics of tactile sensing, thus to give a preliminary explanation to the above question.</p></div><div><h3>Methods</h3><p>This research utilized the Weber-Fechner law to model the tactile sensing as a dynamic low-pass signal filter with varying bandwidths under different compression levels during pulse diagnosis. The model was applied to analyzing the clinical data collected previously by our group. The arterial pressures measured invasively with equipment from 14 patients with aorta coarctation were processed to simulate different pulse manifestations at Cun, Guan, and Chi positions of Cunkou when different compression levels were applied.</p></div><div><h3>Results</h3><p>Due to the characteristics of tactile sensing, significant variations were observed in pulse manifestations at different pulse-depths under the application of changing compression levels; while no such changes in pulse manifestations were observed from the employment of transducer only, without tactile sensing involved. The results explained why different understandings on pulse manifestations were formed between direct pulse-taking technique in TCM and modern sphygmography using transducers. The features of pulse manifestations at Cunkou, using direct pulse-taking technique but at different depths, superficial, middle, and deep positions, respectively, predicted by the developed tactile sensing model were in line with those described in TCM pulse theories.</p></div><div><h3>Conclusion</h3><p>Based on the developed tactile sensing model, this study preliminarily explains the phenomenon that pulse manifestation at Cunkou changes in response to the compression force applied during TCM pulse-taking. Integrating the tactile sensing model with the study of TCM pulse diagnosis opens a new chapter for visualizing and quantitatively interpreting pulse manifestations. This not only expands the scope of pulse diagnosis study effectively, but also provide a scientific basis for further technical upgrading and optimization of existing pulse diagnosis equipment.</p></div>","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000223/pdfft?md5=b7c42f620580affd1cad2c5b27fa558c&pid=1-s2.0-S2589377724000223-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.009
Yarong Ding , Chenlei Xie , Shuihua Feng , Zhonghang Yuan , Wei Wang , Mulin Liu , Zhongzhi Zhou , Li Chen
Objective
To explore the mechanism of Wenyang Shengji Ointment (温阳生肌膏, WYSJO) in the treatment of diabetic wounds from the perspective of network pharmacology, and to verify it by animal experiments.
Methods
The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature were used to screen active compounds in WYSJO and their corresponding targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), DrugBank, PharmGkb, and Therapeutic Target Database (TTD) databases were employed to identify the targets associated with diabetic wounds. Cytoscape 3.9.0 was used to map the active ingredients in WYSJO, which was the diabetic wound target network. Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) platform was utilized to construct protein-protein interaction (PPI) network. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to identify signaling pathways between WYSJO and diabetic wounds. AutoDock 1.5.6 was used for molecular docking of core components in WYSJO to their targets. Eighteen rats were randomly divided into control, model, and WYSJO groups (n = 6). The model and WYSJO groups were used to prepare the model of refractory wounds in diabetes rats. The wound healing was observed on day 0, 5, 9, and 14 after treatment, and the wound tissue morphology was observed by hematoxylin-eosin (HE) staining. The expression levels of core genes were detected by quantitative real-time polymerase chain reaction (qPCR).
Results
A total of 76 active compounds in WYSJO, 206 WYSJO drug targets, 3 797 diabetic wound targets, and 167 diabetic wound associated WYSJO targets were screened out through network pharmacology. With the use of WYSJO-diabetic wound target network, core targets of seven active compounds encompassing quercetin, daidzein, kaempferol, rhamnetin, rhamnocitrin, strictosamide, and diisobutyl phthalate (DIBP) in WYSJO were found. GO enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve lipopolysaccharide, bacteria-derived molecules, metal ions, foreign stimuli, chemical stress, nutrient level, hypoxia, and oxidative stress in the biological processes. KEGG enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve advanced glycation end products (AGE-RAGE), p53, interleukin (IL)-17, tumor necrosis factor (TNF), hypoxia inducible factor-1 (HIF-1), apoptosis, lipid, atherosclerosis, etc. The results of animal experiments showed that WYSJO could significantly accelerate the healing process of diabetic wounds (P < 0.05), alleviate inflammatory response, promote the growth of granulation tissues, and down-regulate the expression levels of eight core genes [histone crotonyltransferase p300 (EP300), protoc gene-oncogene c-Jun (JUN), myelocytomatosis (MYC),
{"title":"Mechanism of Wenyang Shengji Ointment in treating diabetic wounds based on network pharmacology and animal experiments","authors":"Yarong Ding , Chenlei Xie , Shuihua Feng , Zhonghang Yuan , Wei Wang , Mulin Liu , Zhongzhi Zhou , Li Chen","doi":"10.1016/j.dcmed.2024.04.009","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.009","url":null,"abstract":"<div><h3>Objective</h3><p>To explore the mechanism of Wenyang Shengji Ointment (温阳生肌膏, WYSJO) in the treatment of diabetic wounds from the perspective of network pharmacology, and to verify it by animal experiments.</p></div><div><h3>Methods</h3><p>The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature were used to screen active compounds in WYSJO and their corresponding targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), DrugBank, PharmGkb, and Therapeutic Target Database (TTD) databases were employed to identify the targets associated with diabetic wounds. Cytoscape 3.9.0 was used to map the active ingredients in WYSJO, which was the diabetic wound target network. Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) platform was utilized to construct protein-protein interaction (PPI) network. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to identify signaling pathways between WYSJO and diabetic wounds. AutoDock 1.5.6 was used for molecular docking of core components in WYSJO to their targets. Eighteen rats were randomly divided into control, model, and WYSJO groups (<em>n</em> = 6). The model and WYSJO groups were used to prepare the model of refractory wounds in diabetes rats. The wound healing was observed on day 0, 5, 9, and 14 after treatment, and the wound tissue morphology was observed by hematoxylin-eosin (HE) staining. The expression levels of core genes were detected by quantitative real-time polymerase chain reaction (qPCR).</p></div><div><h3>Results</h3><p>A total of 76 active compounds in WYSJO, 206 WYSJO drug targets, 3 797 diabetic wound targets, and 167 diabetic wound associated WYSJO targets were screened out through network pharmacology. With the use of WYSJO-diabetic wound target network, core targets of seven active compounds encompassing quercetin, daidzein, kaempferol, rhamnetin, rhamnocitrin, strictosamide, and diisobutyl phthalate (DIBP) in WYSJO were found. GO enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve lipopolysaccharide, bacteria-derived molecules, metal ions, foreign stimuli, chemical stress, nutrient level, hypoxia, and oxidative stress in the biological processes. KEGG enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve advanced glycation end products (AGE-RAGE), p53, interleukin (IL)-17, tumor necrosis factor (TNF), hypoxia inducible factor-1 (HIF-1), apoptosis, lipid, atherosclerosis, etc. The results of animal experiments showed that WYSJO could significantly accelerate the healing process of diabetic wounds (<em>P</em> < 0.05), alleviate inflammatory response, promote the growth of granulation tissues, and down-regulate the expression levels of eight core genes [histone crotonyltransferase p300 (<em>EP300</em>), protoc gene-oncogene c-Jun (<em>JUN</em>), myelocytomatosis (<em>MYC</em>),","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000284/pdfft?md5=f0f08cbc2e5dce716eac393f21342de7&pid=1-s2.0-S2589377724000284-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.007
Yue Luo , Jianfu Lu , Yunsong Zheng , Lei Bao , Chuanbiao Wen
Objective
This study aimed to explore the influencing factors of dynamic changes in traditional Chinese medicine (TCM) constitution based on general statistics, Apriori-DEMATEL algorithm, and DoWhy causal inference framework methods.
Methods
Dynamic collection of TCM constitution identification data was conducted from the population aged 18 − 60, containing collection time and constitution type, and 11 constitution influencing factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, stress level, living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. General statistical analysis was used to analyze the relative percentage of corresponding influencing factors of different types of constitution changes, the Apriori-DEMATEL algorithm was used to analyze the correlation between 11 constitution influencing factors such as dietary habit and constitution changes, and the DoWhy causal inference framework was used to analyze the causality between dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, explore the frequency of constitution type transformation-change factors, and determine the key influencing factors causing dynamic changes in constitution type.
Results
After preprocessing, 13536 valid data points were obtained. Based on the Apriori-DEMATEL algorithm, the factors were divided into six original factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, and five result factors including living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. Combining with general statistics, we found that among the original factors, changes in dietary habit, sleeping habit, sleeping duration, and stress level had a greater impact on other factors. In the process of constitution conditioning, attention should be paid to these four factors to maintain constitution balance. Among the five result factors, the absolute values of work/life calamity and family atmosphere were relatively large, indicating that these two factors were easily influenced by other factors. The dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level have higher centrality in changes, indicating that these six factors had important in constitution changes. According to the statistical frequency of constitution changes corresponding to each factor, we found that the changes of these six factors accounted for a large proportion of the constitution transformation frequency among Qi deficiency constitution, balanced constitution, and allergic constitution, indicating that the changes of these six factors played an important role in the changes of the three constitution types. Combined with the results of the Apriori-DEMATEL algorithm, and DoWhy
{"title":"Influencing factors analysis of dynamic change of TCM constitution based on multiple methods","authors":"Yue Luo , Jianfu Lu , Yunsong Zheng , Lei Bao , Chuanbiao Wen","doi":"10.1016/j.dcmed.2024.04.007","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.007","url":null,"abstract":"<div><h3>Objective</h3><p>This study aimed to explore the influencing factors of dynamic changes in traditional Chinese medicine (TCM) constitution based on general statistics, Apriori-DEMATEL algorithm, and DoWhy causal inference framework methods.</p></div><div><h3>Methods</h3><p>Dynamic collection of TCM constitution identification data was conducted from the population aged 18 − 60, containing collection time and constitution type, and 11 constitution influencing factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, stress level, living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. General statistical analysis was used to analyze the relative percentage of corresponding influencing factors of different types of constitution changes, the Apriori-DEMATEL algorithm was used to analyze the correlation between 11 constitution influencing factors such as dietary habit and constitution changes, and the DoWhy causal inference framework was used to analyze the causality between dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, explore the frequency of constitution type transformation-change factors, and determine the key influencing factors causing dynamic changes in constitution type.</p></div><div><h3>Results</h3><p>After preprocessing, 13536 valid data points were obtained. Based on the Apriori-DEMATEL algorithm, the factors were divided into six original factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, and five result factors including living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. Combining with general statistics, we found that among the original factors, changes in dietary habit, sleeping habit, sleeping duration, and stress level had a greater impact on other factors. In the process of constitution conditioning, attention should be paid to these four factors to maintain constitution balance. Among the five result factors, the absolute values of work/life calamity and family atmosphere were relatively large, indicating that these two factors were easily influenced by other factors. The dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level have higher centrality in changes, indicating that these six factors had important in constitution changes. According to the statistical frequency of constitution changes corresponding to each factor, we found that the changes of these six factors accounted for a large proportion of the constitution transformation frequency among Qi deficiency constitution, balanced constitution, and allergic constitution, indicating that the changes of these six factors played an important role in the changes of the three constitution types. Combined with the results of the Apriori-DEMATEL algorithm, and DoWhy","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000259/pdfft?md5=6bb35028a5f985897367a78915e65a48&pid=1-s2.0-S2589377724000259-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.010
Tao Li , Xiang Feng , Hui Zhi , Wentao Huang , Jiangshan Li , Wu Li
Objective
To investigate the effects of Tuina targeting different body parts on the behaviors and gut microflora of rat models with valproic acid (VPA)-induced autistic spectrum disorder (ASD).
Methods
Twenty female Sprague Dawley (SD) rats with 12.5 d of pregnancy were randomly divided into VPA model group [intraperitoneal injection of VPA (600 mg/kg), n = 15] and saline group (intraperitoneal injection of equal amount of normal saline, n = 5). The offspring male rats injected with saline were secleted as control group. The offspring male rats injected with VPA were randomly divided into VPA, dorsal, and abdominal groups (n = 7 in each group). On the 21st day after birth, three-chamber social test, open field test, and marble-burying test were carried out to observe the social abilities, anxiety behaviors, and stereotypical behaviors of rats in the four groups. Rats in dorsal and abdominal groups underwent Tuina for 14 d, twice a day. On the 35th day, behavioral tests were conducted again, and intestinal contents were taken for species composition and structural analysis, as well as marker and differential species analysis.
Results
(i) According to behavioral observations, compared with VPA group, the social and movement time in the central open field of rats in dorsal group increased significantly (P < 0.05), and the number of buried marbles decreased markedly (P < 0.01), indicating improvement on their social abilities, anxiety behaviors, and stereotypical behaviors as consequences of dorsal Tuina; and the number of buried marbles was reduced as well in abdominal group when compared with VPA group (P < 0.05), suggesting the improvement on their stereotypical behaviors following abdominal Tuina. In the marble-burying test, the number of marbles buried in dorsal group was less than in abdominal group, and the stereotypical behaviors were improved more significantly (P < 0.05), and there were no significant differences in the three-chamber social and open field tests between the two groups (P >0.05). (ii) In accordance with intestinal microflora detection results, compared with VPA group, both dorsal and abdominal groups showed increased richness (P < 0.05) and elevated diversity (P < 0.05 in dorsal group and P < 0.01 in abdominal group) in intestinal microflora. The results of differential analysis indicated that at the phylum level, compared with VPA group, the relative abundance of Firmicutes in rats in abdominal group showed a significant reduction trend (P < 0.05); at the genus level, compared with VPA group, the relative abundance of Lactobacillus in rats in dorsal and abdominal groups decreased significantly (P < 0.05). Dorsal group also showed significant increase in the genus Blautia in the analysis of
{"title":"Effects of Tuina targeting different body parts on the behaviors and gut microflora of autistic spectrum disorder rat models","authors":"Tao Li , Xiang Feng , Hui Zhi , Wentao Huang , Jiangshan Li , Wu Li","doi":"10.1016/j.dcmed.2024.04.010","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.010","url":null,"abstract":"<div><h3>Objective</h3><p>To investigate the effects of Tuina targeting different body parts on the behaviors and gut microflora of rat models with valproic acid (VPA)-induced autistic spectrum disorder (ASD).</p></div><div><h3>Methods</h3><p>Twenty female Sprague Dawley (SD) rats with 12.5 d of pregnancy were randomly divided into VPA model group [intraperitoneal injection of VPA (600 mg/kg), <em>n</em> = 15] and saline group (intraperitoneal injection of equal amount of normal saline, <em>n</em> = 5). The offspring male rats injected with saline were secleted as control group. The offspring male rats injected with VPA were randomly divided into VPA, dorsal, and abdominal groups (<em>n</em> = 7 in each group). On the 21st day after birth, three-chamber social test, open field test, and marble-burying test were carried out to observe the social abilities, anxiety behaviors, and stereotypical behaviors of rats in the four groups. Rats in dorsal and abdominal groups underwent Tuina for 14 d, twice a day. On the 35th day, behavioral tests were conducted again, and intestinal contents were taken for species composition and structural analysis, as well as marker and differential species analysis.</p></div><div><h3>Results</h3><p>(i) According to behavioral observations, compared with VPA group, the social and movement time in the central open field of rats in dorsal group increased significantly (<em>P</em> < 0.05), and the number of buried marbles decreased markedly (<em>P</em> < 0.01), indicating improvement on their social abilities, anxiety behaviors, and stereotypical behaviors as consequences of dorsal Tuina; and the number of buried marbles was reduced as well in abdominal group when compared with VPA group (<em>P</em> < 0.05), suggesting the improvement on their stereotypical behaviors following abdominal Tuina. In the marble-burying test, the number of marbles buried in dorsal group was less than in abdominal group, and the stereotypical behaviors were improved more significantly (<em>P</em> < 0.05), and there were no significant differences in the three-chamber social and open field tests between the two groups (<em>P</em> >0.05). (ii) In accordance with intestinal microflora detection results, compared with VPA group, both dorsal and abdominal groups showed increased richness (<em>P</em> < 0.05) and elevated diversity (<em>P</em> < 0.05 in dorsal group and <em>P</em> < 0.01 in abdominal group) in intestinal microflora. The results of differential analysis indicated that at the phylum level, compared with VPA group, the relative abundance of <em>Firmicutes</em> in rats in abdominal group showed a significant reduction trend (<em>P</em> < 0.05); at the genus level, compared with VPA group, the relative abundance of <em>Lactobacillus</em> in rats in dorsal and abdominal groups decreased significantly (<em>P</em> < 0.05). Dorsal group also showed significant increase in the genus <em>Blautia</em> in the analysis of","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000296/pdfft?md5=96632c630b5422ff200694380a91abff&pid=1-s2.0-S2589377724000296-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To clarify the distribution of traditional Chinese medicine (TCM) pattern and its associated risk factors after percutaneous coronary intervention (PCI), and evaluate the reporting quality of existing studies to guide future research standardization.
Methods
English databases including PubMed, Cochrane Library, and Web of Science, as well as Chinese databases including China National Knowledge Infrastructure (CNKI), China Scientific Journal Database (VIP), and Wanfang Database were searched to retrieve papers about PCI. The time span for the paper retrieval was set from the foundation of the databases to October 1, 2023. Statistical analyses were performed using Stata 12 and Python (V 3.9). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement was used to assess the reporting quality of included studies.
Results
Overall, 1 356 articles were selected, and 40 cross-sectional studies were included with 10 270 participants. The most common TCM patterns before, one to two weeks after, and six months to one year after PCI was Qi stagnation and blood stasis (n = 261, 36.45%), intertwined phlegm and blood stasis (n = 109, 27.18%), and Qi deficiency and blood stasis (n = 645, 37.03%), respectively. Smoking [odds ratio (OR) = 1.15, 95% confidence interval (CI) (0.83 – 1.47), I2= 24.7%, P = 0.257], pattern of congealing cold and Qi stagnation [OR = 4.62, 95% CI (1.37 – 7.86), I2 = 61.6%, P = 0.074], and low-density lipoprotein (LDL) [OR = 1.38, 95% CI (0.92 – 1.85), I2= 12.2%, P = 0.286] were risk factors for restenosis. Hypertension [OR = 7.26, 95% CI (3.54 – 14.88), I2= 91.6%, P = 0.001], and overweight [i.e., body mass index (BMI) > 23] [OR = 1.20, 95% CI (1.07 – 1.35), I2= 85.3%, P = 0.009] were significant risk factors of concomitant anxiety.
Conclusion
This systematic review and meta-analysis revealed that patients with different TCM pattern types have distinct characteristics and risk factors after PCI. More high-quality studies are warranted to provide supportive evidence for future research and clinical practice.
{"title":"Distribution of traditional Chinese medicine pattern types and prognostic risk factors in patients undergoing percutaneous coronary intervention (PCI): a systematic review and meta-analysis","authors":"L.I. Jieyun , H.O.N.G. Leixin , L.I.N. Jiekee , X.I.A. Yumo , X.I.A.O. Xin’ang , X.U. Zhaoxia","doi":"10.1016/j.dcmed.2024.04.003","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.003","url":null,"abstract":"<div><h3>Objective</h3><p>To clarify the distribution of traditional Chinese medicine (TCM) pattern and its associated risk factors after percutaneous coronary intervention (PCI), and evaluate the reporting quality of existing studies to guide future research standardization.</p></div><div><h3>Methods</h3><p>English databases including PubMed, Cochrane Library, and Web of Science, as well as Chinese databases including China National Knowledge Infrastructure (CNKI), China Scientific Journal Database (VIP), and Wanfang Database were searched to retrieve papers about PCI. The time span for the paper retrieval was set from the foundation of the databases to October 1, 2023. Statistical analyses were performed using Stata 12 and Python (V 3.9). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement was used to assess the reporting quality of included studies.</p></div><div><h3>Results</h3><p>Overall, 1 356 articles were selected, and 40 cross-sectional studies were included with 10 270 participants. The most common TCM patterns before, one to two weeks after, and six months to one year after PCI was Qi stagnation and blood stasis (<em>n</em> = 261, 36.45%), intertwined phlegm and blood stasis (<em>n</em> = 109, 27.18%), and Qi deficiency and blood stasis (<em>n</em> = 645, 37.03%), respectively. Smoking [odds ratio (OR) = 1.15, 95% confidence interval (CI) (0.83 – 1.47), <em>I</em><sup><em>2</em></sup>= 24.7%, <em>P</em> = 0.257], pattern of congealing cold and Qi stagnation [OR = 4.62, 95% CI (1.37 – 7.86), <em>I</em><sup>2</sup> = 61.6%, <em>P</em> = 0.074], and low-density lipoprotein (LDL) [OR = 1.38, 95% CI (0.92 – 1.85), <em>I</em><sup><em>2</em></sup>= 12.2%, <em>P</em> = 0.286] were risk factors for restenosis. Hypertension [OR = 7.26, 95% CI (3.54 – 14.88), <em>I</em><sup><em>2</em></sup>= 91.6%, <em>P</em> = 0.001], and overweight [i.e., body mass index (BMI) > 23] [OR = 1.20, 95% CI (1.07 – 1.35), <em>I</em><sup><em>2</em></sup>= 85.3%, <em>P</em> = 0.009] were significant risk factors of concomitant anxiety.</p></div><div><h3>Conclusion</h3><p>This systematic review and meta-analysis revealed that patients with different TCM pattern types have distinct characteristics and risk factors after PCI. More high-quality studies are warranted to provide supportive evidence for future research and clinical practice.</p></div>","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000211/pdfft?md5=a1863451f5f32dfef9fd5f6bac5de423&pid=1-s2.0-S2589377724000211-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.001
L.U. Shan , P.E.N.G. Qinghua
{"title":"Thoughts on the system construction of digital Chinese medicine","authors":"L.U. Shan , P.E.N.G. Qinghua","doi":"10.1016/j.dcmed.2024.04.001","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.001","url":null,"abstract":"","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000193/pdfft?md5=ba94ffc342adf0a345a1c3b422665eec&pid=1-s2.0-S2589377724000193-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To investigate the correlation between tongue and pulse indicators and the outcome of live birth in patients undergoing frozen-thawed embryo transfer (FET), as well as the association between these indicators and patients’ endocrine parameters.
Methods
This study was conducted at Reproductive Medicine Center, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China, from March 8, 2021 to January 5, 2022. Patients undergoing FET were divided into live birth and non-live birth groups according to their live birth outcome. The differences between the endocrine parameters [basic follicle stimulating hormone (b FSH), basic luteinizing hormone (b LH), basic estradiol (b E2), basic progesterone (b P), basal endometrial thickness, follicle stimulating hormone (FSH) on endometrial transition day, luteinizing hormone (LH) on endometrial transition day, estradiol (E2) on endometrial transition day, progesterone (P) on endometrial transition day, and endometrial thickness on endometrial transition day] and the tongue and pulse indicators [tongue body (TB)-L, TB-a, TB-b, tongue coating (TC)-L, TC-a, TC-b, perAll, perPart, h1, h4, h5, t1, h1/t1, and h4/h1] of patients in the two groups were analyzed, with the correlation between these variables analyzed as well using Spearman’s correlation coefficient. Multivariate logistic regression was employed to identify the influential factors in the live birth prediction models across various datasets, including Model 1 consisting of endocrine indicators only, Model 2 solely consisting of tongue and pulse indicators, and Model 3 consisting of both tongue, pulse, and endocrine indicators, as well as to evaluate efficacy of the models derived from different datasets.
Results
This study included 78 patients in live birth group and 144 patients in non-live birth group. Compared with non-live birth group, live birth group exhibited higher levels of TB-L (P = 0.01) and TB-a (P = 0.04), while demonstrated lower levels of b FSH (P = 0.01), perAll (P = 0.04), and h4/h1 (P = 0.03). The Spearman’s correlation coefficient analysis revealed statistically significant correlation (P < 0.05) between TB-L, TB-b, TC-L, TC-b, perAll, perPart, h4, h5, t1, h1/t1 and b FSH, b LH, basal endometrial thickness, LH on endometrial transition day, E2 on endometrial transition day, P on endometrial transition day, and endometrial thickness on endometrial transition day in live birth group. The multivariate logistic regression analysis showed that the prediction Model 3 for live birth outcome [area under the curve (AUC): 0.917, 95% confidence interval (CI): 0.863 − 0.971, P
{"title":"Correlation between tongue and pulse indicators and the outcome of live birth in frozen-thawed embryo transfer","authors":"W.A.N.G. Jinluan , G.U.O. Zhiling , Z.H.A.N.G. Qinhua , Y.A.N. Hua , T.U. Liping , X.U. Jiatuo","doi":"10.1016/j.dcmed.2024.04.008","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.008","url":null,"abstract":"<div><h3>Objective</h3><p>To investigate the correlation between tongue and pulse indicators and the outcome of live birth in patients undergoing frozen-thawed embryo transfer (FET), as well as the association between these indicators and patients’ endocrine parameters.</p></div><div><h3>Methods</h3><p>This study was conducted at Reproductive Medicine Center, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China, from March 8, 2021 to January 5, 2022. Patients undergoing FET were divided into live birth and non-live birth groups according to their live birth outcome. The differences between the endocrine parameters [basic follicle stimulating hormone (b FSH), basic luteinizing hormone (b LH), basic estradiol (b E<sub>2</sub>), basic progesterone (b P), basal endometrial thickness, follicle stimulating hormone (FSH) on endometrial transition day, luteinizing hormone (LH) on endometrial transition day, estradiol (E<sub>2</sub>) on endometrial transition day, progesterone (P) on endometrial transition day, and endometrial thickness on endometrial transition day] and the tongue and pulse indicators [tongue body (TB)-L, TB-a, TB-b, tongue coating (TC)-L, TC-a, TC-b, perAll, perPart, h<sub>1</sub>, h<sub>4</sub>, h<sub>5</sub>, t<sub>1</sub>, h<sub>1</sub>/t<sub>1</sub>, and h<sub>4</sub>/h<sub>1</sub>] of patients in the two groups were analyzed, with the correlation between these variables analyzed as well using Spearman’s correlation coefficient. Multivariate logistic regression was employed to identify the influential factors in the live birth prediction models across various datasets, including Model 1 consisting of endocrine indicators only, Model 2 solely consisting of tongue and pulse indicators, and Model 3 consisting of both tongue, pulse, and endocrine indicators, as well as to evaluate efficacy of the models derived from different datasets.</p></div><div><h3>Results</h3><p>This study included 78 patients in live birth group and 144 patients in non-live birth group. Compared with non-live birth group, live birth group exhibited higher levels of TB-L (<em>P</em> = 0.01) and TB-a (<em>P</em> = 0.04), while demonstrated lower levels of b FSH (<em>P</em> = 0.01), perAll (<em>P</em> = 0.04), and h<sub>4</sub>/h<sub>1</sub> (<em>P</em> = 0.03). The Spearman’s correlation coefficient analysis revealed statistically significant correlation (<em>P</em> < 0.05) between TB-L, TB-b, TC-L, TC-b, perAll, perPart, h<sub>4</sub>, h<sub>5</sub>, t<sub>1</sub>, h<sub>1</sub>/t<sub>1</sub> and b FSH, b LH, basal endometrial thickness, LH on endometrial transition day, E<sub>2</sub> on endometrial transition day, P on endometrial transition day, and endometrial thickness on endometrial transition day in live birth group. The multivariate logistic regression analysis showed that the prediction Model 3 for live birth outcome [area under the curve (AUC): 0.917, 95% confidence interval (CI): 0.863 − 0.971, <em>P</em","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000260/pdfft?md5=636f0a8b6487f68da3c015cb96446878&pid=1-s2.0-S2589377724000260-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.005
Tsz Ho Wong , Junyi Wei , Haiyong Chen , Bacon Fung Leung Ng
Objective
The unintentional retention of needles in patients can lead to severe consequences. To enhance acupuncture safety, the study aimed to develop a deep learning-based cloud system for automated process of counting acupuncture needles.
Methods
This project adopted transfer learning from a pre-trained Oriented Region-based Convolutional Neural Network (Oriented R-CNN) model to develop a detection algorithm that can automatically count the number of acupuncture needles in a camera picture. A training set with 590 pictures and a validation set with 1 025 pictures were accumulated for fine-tuning. Then, we deployed the MMRotate toolbox in a Google Colab environment with a NVIDIA Tesla T4 Graphics processing unit (GPU) to carry out the training task. Furthermore, we integrated the model with a newly-developed Telegram bot interface to determine the accuracy, precision, and recall of the needling counting system. The end-to-end inference time was also recorded to determine the speed of our cloud service system.
Results
In a 20-needle scenario, our Oriented R-CNN detection model has achieved an accuracy of 96.49%, precision of 99.98%, and recall of 99.84%, with an average end-to-end inference time of 1.535 s
Conclusion
The speed, accuracy, and reliability advancements of this cloud service system innovation have demonstrated its potential of using object detection technique to improve acupuncture practice based on deep learning.
{"title":"A novel deep learning based cloud service system for automated acupuncture needle counting: a strategy to improve acupuncture safety","authors":"Tsz Ho Wong , Junyi Wei , Haiyong Chen , Bacon Fung Leung Ng","doi":"10.1016/j.dcmed.2024.04.005","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.005","url":null,"abstract":"<div><h3>Objective</h3><p>The unintentional retention of needles in patients can lead to severe consequences. To enhance acupuncture safety, the study aimed to develop a deep learning-based cloud system for automated process of counting acupuncture needles.</p></div><div><h3>Methods</h3><p>This project adopted transfer learning from a pre-trained Oriented Region-based Convolutional Neural Network (Oriented R-CNN) model to develop a detection algorithm that can automatically count the number of acupuncture needles in a camera picture. A training set with 590 pictures and a validation set with 1 025 pictures were accumulated for fine-tuning. Then, we deployed the MMRotate toolbox in a Google Colab environment with a NVIDIA Tesla T4 Graphics processing unit (GPU) to carry out the training task. Furthermore, we integrated the model with a newly-developed Telegram bot interface to determine the accuracy, precision, and recall of the needling counting system. The end-to-end inference time was also recorded to determine the speed of our cloud service system.</p></div><div><h3>Results</h3><p>In a 20-needle scenario, our Oriented R-CNN detection model has achieved an accuracy of 96.49%, precision of 99.98%, and recall of 99.84%, with an average end-to-end inference time of 1.535 s</p></div><div><h3>Conclusion</h3><p>The speed, accuracy, and reliability advancements of this cloud service system innovation have demonstrated its potential of using object detection technique to improve acupuncture practice based on deep learning.</p></div>","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589377724000235/pdfft?md5=5ee6e77d5a36cf17394eceb01137dc14&pid=1-s2.0-S2589377724000235-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1016/j.dcmed.2024.04.002
X.U. Jiatuo, J.I.A.N.G. Tao, L.I.U. Shi
Image-based intelligent diagnosis represents a trending research direction in the field of tongue diagnosis in traditional Chinese medicine (TCM). In recent years, machine learning techniques, including convolutional neural networks (CNNs) and Transformers, have been widely used in the analysis of medical images, such as computed tomography (CT) and nuclear magnetic resonance imaging (MRI). These techniques have significantly enhanced the efficiency and accuracy of decision-making in TCM practices. Advanced artificial intelligence (AI) technologies have also provided new opportunities for the research and development of medical equipment and TCM tongue diagnosis, resulting in improved standardization and intelligence of the tongue diagnostic procedures. Although traditional image analysis methods could transform tongue images into scientific and analyzable data, recognizing and analyzing images that capture complicated tongue features such as tooth-marked tongue, tongue spots and prickles, fissured tongue, variations in coating thickness, tongue texture (curdy and greasy), and tongue presence (peeled coating) continues posing significant challenges in contemporary tongue diagnosis research. Therefore, the employment of machine learning techniques in the analysis of tongue shape and texture features as well as their applications in TCM diagnosis is the focus of this study. In the study, both traditional and deep learning image analysis techniques were summarized and analyzed to figure out their value in predicting disease risks by observing the tongue shapes and textures, aiming to open a new chapter for the development and application of AI in TCM tongue diagnosis research. In short, the combination of TCM tongue diagnosis and AI technologies, will not only enhance the scientific basis of tongue diagnosis but also improve its clinical applicability, thereby advancing the modernization of TCM diagnostic and therapeutic practices.
{"title":"Research status and prospect of tongue image diagnosis analysis based on machine learning","authors":"X.U. Jiatuo, J.I.A.N.G. Tao, L.I.U. Shi","doi":"10.1016/j.dcmed.2024.04.002","DOIUrl":"https://doi.org/10.1016/j.dcmed.2024.04.002","url":null,"abstract":"<div><p>Image-based intelligent diagnosis represents a trending research direction in the field of tongue diagnosis in traditional Chinese medicine (TCM). In recent years, machine learning techniques, including convolutional neural networks (CNNs) and Transformers, have been widely used in the analysis of medical images, such as computed tomography (CT) and nuclear magnetic resonance imaging (MRI). These techniques have significantly enhanced the efficiency and accuracy of decision-making in TCM practices. Advanced artificial intelligence (AI) technologies have also provided new opportunities for the research and development of medical equipment and TCM tongue diagnosis, resulting in improved standardization and intelligence of the tongue diagnostic procedures. Although traditional image analysis methods could transform tongue images into scientific and analyzable data, recognizing and analyzing images that capture complicated tongue features such as tooth-marked tongue, tongue spots and prickles, fissured tongue, variations in coating thickness, tongue texture (curdy and greasy), and tongue presence (peeled coating) continues posing significant challenges in contemporary tongue diagnosis research. Therefore, the employment of machine learning techniques in the analysis of tongue shape and texture features as well as their applications in TCM diagnosis is the focus of this study. In the study, both traditional and deep learning image analysis techniques were summarized and analyzed to figure out their value in predicting disease risks by observing the tongue shapes and textures, aiming to open a new chapter for the development and application of AI in TCM tongue diagnosis research. In short, the combination of TCM tongue diagnosis and AI technologies, will not only enhance the scientific basis of tongue diagnosis but also improve its clinical applicability, thereby advancing the modernization of TCM diagnostic and therapeutic practices.</p></div>","PeriodicalId":33578,"journal":{"name":"Digital Chinese Medicine","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S258937772400020X/pdfft?md5=ea933f4c35060e5cb6d1f7b9d1bece79&pid=1-s2.0-S258937772400020X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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