[Construction of an artificial intelligence-assisted system for auxiliary detection of auricular point features based on the YOLO neural network].

The key-point detection model of 21 common auricular points based on YOLOv8n exhibits the excellent predictive performance, which is capable of rapidly and automatically locating and classifying auricular points.

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Publication Details

Journal
PubMed
Published
2025-04-12
DOI
https://doi.org/10.13703/j.0255-2930.20240611-0001
Primary Topic
Healthcare Systems and Public Health
Type
article
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article

[Construction of an artificial intelligence-assisted system for auxiliary detection of auricular point features based on the YOLO neural network].

Kaijian Xia, Yanting Zhou, Ganhong Wang, Zihao Zhang et al.
PubMed
Healthcare Systems and Public Health
article

[Construction of an artificial intelligence-assisted system for auxiliary detection of auricular point features based on the YOLO neural network].

Kaijian Xia, Yanting Zhou, Ganhong Wang, Zihao Zhang, Jian Chen, Meijuan Xi
article en

Abstract

The key-point detection model of 21 common auricular points based on YOLOv8n exhibits the excellent predictive performance, which is capable of rapidly and automatically locating and classifying auricular points.

PubMedVol. 45(4)
WuXi AppTec (China) (CN), Changshu No.1 People's Hospital (CN), Artificial Intelligence in Medicine (Canada) (CA)
Healthcare Systems and Public Health
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[Construction of an artificial intelligence-assisted system for auxiliary detection of auricular point features based on the YOLO neural network]. — Kaijian Xia, Yanting Zhou, et al. · PubMed (2025) | TGRS Research Map | TGRS