ArticleChinese medicine2025
Study on a Traditional Chinese Medicine constitution recognition model using tongue image characteristics and deep learning: a prospective dual-center investigation.
Article in Chinese medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Large language models linking traditional Chinese medicine knowledge and clinical practice.Chinese medicine · 2026Review
- From Traditional Inspection to Quantitative Imaging: Tongue and Facial Color Features for Automated Machine Learning-Driven Depression and Schizophrenia Classification.Behavioral sciences (Basel, Switzerland) · 2026Article
- Association between the fear of cancer recurrence and Traditional Chinese Medicine constitution in breast cancer patients: a cross-sectional study.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2026Article
- Tongue color tones in Traditional Chinese Medicine correlate with liver histology of metabolic dysfunction-associated steatohepatitis in morbidly obese patients undergoing metabolic and bariatric surgery.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2026Article
- Application of a Large Visual Language Model on Tongue Image Description Generation and Physical Constitution Reasoning in Traditional Chinese Medicine (TongueVLM): Model Development and Validation Study.JMIR medical informatics · 2026Article
- Tongue Characteristics and Musculoskeletal Pain in Patients with Type 2 Diabetes Mellitus: A Principal Component and Latent Profile Analysis.Journal of pain research · 2026Article
- A cross-modal feature fusion model integrating tongue image phenotypes and accessible endocrine profiles for the screening of polycystic ovary syndrome.Frontiers in medicine · 2026Article
- Deep learning approach for objective differentiation of kidney deficiency syndrome in reproductive age females: a tongue-face fusion model.Frontiers in physiology · 2025Article
- Constructing and validating vision transformer-based assisted detection models for atrophic gastritis: A retrospective study.Science progressArticle
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7 authors.
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Abstract
purposeThe objective of this study was to develop a quantitatively analyzed Traditional Chinese Medicine (TCM) constitution recognition model utilizing tongue fusion features and deep learning techniques.
methodsA prospective investigation was conducted on participants undergoing TCM constitution assessment at two medical centers. Tongue images and corresponding TCM constitution data were collected from 1374 participants using specialized equipment. Both traditional and deep features were extracted from these images. Significant features associated with constitutional characteristics were identified through LASSO regression and Random Forest (RF). Eight machine learning algorithms were employed to construct and evaluate the efficacy of the models. The highest-performing model was selected as the foundational classifier for developing an integrated tongue image feature model. Model performance was comprehensively evaluated using accuracy, precision, recall, F1 score, and area under the curve (AUC).
resultsAnalysis revealed 11 critical traditional tongue image features and 26 deep tongue image features. Three datasets were constructed: traditional tongue image features, deep tongue image features, and a fusion feature dataset incorporating both. The multilayer perceptron (MLP) model combining traditional and deep features demonstrated superior performance in TCM constitution classification compared to single-feature models. In the training phase, the model achieved an accuracy (ACC) of 0.893 and an AUC of 0.948. On the test set, it achieved an ACC of 0.837 and an AUC of 0.898, with sensitivity and specificity of 0.680 and 0.930, respectively, indicating excellent generalization ability.
conclusionsThis study successfully developed an intelligent TCM constitution recognition model that overcomes the limitations of traditional methods and validates the value of tongue images for accurate constitution recognition.
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