Study on the Correlation Between Machine Learning-Based Tongue Features of Healthy Individuals in the Real World and Age and Gender
- VernacularTitle:基于机器学习的真实世界健康人舌象与年龄及性别相关性研究
- Author:
Jiqing WANG
1
;
Lei ZHANG
1
;
Shifen XU
1
;
Yiqun MI
1
Author Information
- Publication Type:Journal Article
- Keywords: Real-world data; Machine learning; Tongue image and age relationship; Tongue image and gender relationship
- From: World Science and Technology-Modernization of Traditional Chinese Medicine 2024;26(11):2806-2814
- CountryChina
- Language:Chinese
- Abstract: Objective Validate the correlation between tongue features and age and gender by utilizing real-world tongue image data from healthy individuals.Methods Establishing,training,and validating a model using artificial intelligence image acquisition techniques and machine learning tools.Results ①Artificial intelligence has achieved the digitization and standardization of Traditional Chinese Medicine tongue diagnosis data,establishing a database of Traditional Chinese Medicine tongue diagnosis(n=56573).②A highly accurate random forest model has demonstrated the correlation between tongue features and gender and age.③Further selection of key factors that show differences in tongue features between different age groups and genders.④Machine learning artificial neural network models were trained,tested,and validated(training set R2=0.8772,validation set R2=0.8715,test set R2=0.8707,AUC=89.5％),demonstrating excellent accuracy.Conclusion Machine learning validation using real-world data has confirmed that tongue features change with age.Additionally,analysis of large-scale real-world data has revealed that there are different tongue features associated with gender differences.
