ArticleBioMed research international2021
A New Method for Syndrome Classification of Non-Small-Cell Lung Cancer Based on Data of Tongue and Pulse with Machine Learning.
Article in BioMed research international, 2021. 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.
- Cross-modal attention model integrating tongue images and descriptions: a novel intelligent TCM approach for pathological organ diagnosis.Frontiers in physiology · 2025Article
- Developing a transparent reporting tool for AI-based diagnostic prediction models of disease and syndrome in Chinese medicine: a Delphi protocol.Frontiers in digital health · 2025Article
- Syndrome Differentiation and Treatment of Psoriasis by Traditional Chinese Medicines: An Integrating Study of Multi-Omics Analysis and Experimental Validation.Journal of inflammation research · 2025Article
- Machine learning classification of polycystic ovary syndrome based on radial pulse wave analysis.BMC complementary medicine and therapies · 2023Article
- Current status and trends of artificial intelligence research on the four traditional Chinese medicine diagnostic methods: a scientometric study.Annals of translational medicine · 2023Article
- Article
- A lung cancer risk warning model based on tongue images.Frontiers in physiology · 2023Article
- Development, Validation and Comparison of Artificial Neural Network and Logistic Regression Models Predicting Eosinophilic Chronic Rhinosinusitis With Nasal Polyps.Allergy, asthma & immunology research · 2023Article
- A Landscape of Metabonomics for Intermingled Phlegm and Blood Stasis and Its Concurrent Syndromes in Stable Angina Pectoris of Coronary Heart Disease.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
10 authors.
Funding
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Abstract
objectiveTo explore the data characteristics of tongue and pulse of non-small-cell lung cancer with Qi deficiency syndrome and Yin deficiency syndrome, establish syndrome classification model based on data of tongue and pulse by using machine learning methods, and evaluate the feasibility of syndrome classification based on data of tongue and pulse.
methodsWe collected tongue and pulse of non-small-cell lung cancer patients with Qi deficiency syndrome (
resultsSignificant difference indices of tongue diagnosis between Qi deficiency syndrome and Yin deficiency syndrome were TB-a, TB-S, TB-Cr, TC-a, TC-S, TC-Cr, perAll, and the tongue coating texture indices including TC-CON, TC-ASM, TC-MEAN, and TC-ENT. Significant difference indices of pulse diagnosis were t
conclusionsIt was feasible to use tongue data and pulse data as one of the objective diagnostic basis in Qi deficiency syndrome and Yin deficiency syndrome of non-small-cell lung cancer.
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