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Credits

This page lists datasets and sources used to train and validate the model.

TCM-Tongue Dataset

We use the TCM-Tongue dataset proposed by Jin et al., consisting of 6,719 standardized tongue images annotated by licensed TCM practitioners, released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Citation: Jin, Xue-bo; Gao, Longfei; Tong, Anshuo; Chen, Zhengyang; Kong, Jianlei; Sun, Ning; Ma, Huijun; Wang, Qiang; Bai, Yu-Ting; Su, Tingli. TCM-Tongue: A Standardized Tongue Image Dataset with Pathological Annotations for AI-Assisted TCM Analysis (2025). Licensed under CC BY 4.0.

Auricular Acupoint Detection

The ear acupoint detection model is based on the YOLOv11 system for keypoint detection of auricular acupuncture points developed by Wang et al. (2025), published in Frontiers in Physiology.

Citation: Wang G, Yin L, Zhang H, Xia K, Su Y and Chen J (2025) A YOLOv11-based AI system for keypoint detection of auricular acupuncture points in traditional Chinese medicine. Licensed under CC BY 4.0.