首页|期刊导航|结合医学学报（英文版）|A hierarchical and interpretable machine learning model for acupoint determination

A hierarchical and interpretable machine learning model for acupoint determination

Hang Yang Ren Wu Mitsuru Nakata Qi-wei Ge

结合医学学报（英文版）2026，Vol.24Issue(3)：340-351,12.

结合医学学报（英文版）2026，Vol.24Issue(3)：340-351,12.DOI:10.1016/j.joim.2026.01.003

A hierarchical and interpretable machine learning model for acupoint determination

Hang Yang ¹Ren Wu ²Mitsuru Nakata ³Qi-wei Ge⁴

作者信息

1. The Graduate School of East Asian Studies,Yamaguchi University,Yamaguchi-shi 753-8514,Yamaguchi,Japan
2. Faculty of Information Science,Shunan University,Shunan-shi 745-8566,Yamaguchi,Japan
3. Faculty of Education,Yamaguchi University,Yamaguchi-shi 753-8513,Yamaguchi,Japan
4. Yamaguchi University,Yamaguchi-shi 753-8511,Yamaguchi,Japan
折叠

摘要

关键词

Machine learning/Acupuncture and moxibustion/Acupoint prescription/Hierarchical classification

Key words

Machine learning/Acupuncture and moxibustion/Acupoint prescription/Hierarchical classification

引用本文复制引用

Hang Yang,Ren Wu,Mitsuru Nakata,Qi-wei Ge..A hierarchical and interpretable machine learning model for acupoint determination[J].结合医学学报（英文版）,2026,24(3):340-351,12.

基金项目

This work was supported by Grants-in-Aid for Scientific Research(KAKENHI)from JSPS(No.23K20390)and Support for Pioneering Research Initiated by the Next Generation(SPRING)from JST(No.JPMJSP2111). （KAKENHI）

结合医学学报（英文版）

ISSN：2095-4964

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