ArticleComputational and mathematical methods in medicine2017
Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.
Article in Computational and mathematical methods in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Current Status of Objectification of Four Diagnostic Methods on Constitution Recognition of Chinese Medicine.Chinese journal of integrative medicine · 2022Pooled it
- Application of machine learning methods in prediction of the body constitution types and transformation trends of traditional Chinese medicine: from the datasets of questionnaire survey on elderly people in Southwest China.Frontiers in medicine · 2026Article
- Traditional Chinese Medicine Constitution Identification Based on Objective Facial and Tongue Features: A Delphi Study and a Diagnostic Nomogram for Blood Stasis Constitution.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine.Evidence-based complementary and alternative medicine : eCAM · 2022Review
- Personalized Body Constitution Inquiry Based on Machine Learning.Journal of healthcare engineering · 2020Article
- Multilevel and Multiscale Feature Aggregation in Deep Networks for Facial Constitution Classification.Computational and mathematical methods in medicine · 2019Article
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Authors and funding
8 authors.
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Abstract
Body constitution classification is the basis and core content of traditional Chinese medicine constitution research. It is to extract the relevant laws from the complex constitution phenomenon and finally build the constitution classification system. Traditional identification methods have the disadvantages of inefficiency and low accuracy, for instance, questionnaires. This paper proposed a body constitution recognition algorithm based on deep convolutional neural network, which can classify individual constitution types according to face images. The proposed model first uses the convolutional neural network to extract the features of face image and then combines the extracted features with the color features. Finally, the fusion features are input to the Softmax classifier to get the classification result. Different comparison experiments show that the algorithm proposed in this paper can achieve the accuracy of 65.29% about the constitution classification. And its performance was accepted by Chinese medicine practitioners.
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