Predicting acupuncture efficacy for functional dyspepsia based on routine clinical features: a machine learning study in the framework of predictive, preventive, and personalized medicine

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Yin, Tao;Zheng, Hui;Ma, Tingting;Tian, Xiaoping;Xu, Jing;...

通讯作者：

Liang, Fanrong;Zeng, Fang

作者机构：

[Zeng, Fang; Lan, Lei; Tang, Yong; Liang, Fanrong; Zeng, F; Sun, Ruirui; Xu, Jing; Tian, Xiaoping; Yin, Tao; Zheng, Hui] Chengdu Univ Tradit Chinese Med, Acupuncture & Tuina Sch, Teaching Hosp 3, Chengdu 610075, Sichuan, Peoples R China.

[Zeng, Fang; Lan, Lei; Sun, Ruirui; Yin, Tao] Chengdu Univ Tradit Chinese Med, Acupuncture Brain Sci Res Ctr, Chengdu 610075, Sichuan, Peoples R China.

[Ma, Tingting] Hosp Chengdu Univ Tradit Chinese Med, Chengdu 610075, Sichuan, Peoples R China.

[Li, Ying] Chengdu Univ Tradit Chinese Med, Grad Sch, Chengdu 610075, Sichuan, Peoples R China.

[Liu, Mailan] Hunan Univ Chinese Med, Acupuncture & Tuina Sch, Changsha 410208, Hunan, Peoples R China.

通讯机构：

[Liang, FR; Zeng, F; Zeng, Fang] C

Chengdu Univ Tradit Chinese Med, Acupuncture & Tuina Sch, Teaching Hosp 3, Chengdu 610075, Sichuan, Peoples R China.

Chengdu Univ Tradit Chinese Med, Acupuncture Brain Sci Res Ctr, Chengdu 610075, Sichuan, Peoples R China.

语种：

英文

关键词：

Predictive preventive personalized medicine (PPPM/3PM);Healthcare;Acupuncture;Functional dyspepsia;Efficacy prediction;Precision medicine;Machine learning;Artificial intelligence;Support vector machine

期刊：

EPMA Journal

ISSN：

1878-5077

年：

2022

卷：

期：

页码：

137-147

DOI：

10.1007/s13167-022-00271-8

基金类别：

The study was financially supported by the National Natural Science Foundation of China (No. 81973960, 81622052, 81473602), the National Basic Research Program of China (973 Program) (No. 2012CB518500, 2012CB518501), and the Sichuan Science and Technology Program (No. 2019JDTD0011). National Basic Research Program of China (973 Program), No. 2012CB518500, Fanrong Liang, 2012CB518501, Fanrong Liang, National Natural Science Foundation of China, No. 81973960, Fang Zeng, 81622052, Fang Zeng, 81473602, Fang Zeng, Sichuan Science and Technology Program, No. 2019JDTD0011, Fang Zeng

机构署名：

本校为其他机构

院系归属：

针灸推拿与康复学院

摘要：

Background Acupuncture is safe and effective for functional dyspepsia (FD), while its efficacy varies among individuals. Predicting the response of different FD patients to acupuncture treatment in advance and therefore administering the tailored treatment to the individual is consistent with the principle of predictive, preventive, and personalized medicine (PPPM/3PM). In the current study, the individual efficacy prediction models were developed based on the support vector machine (SVM) algorithm and routine clinical features, aiming to predict the efficacy of acupuncture in treating FD and ...

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Predicting acupuncture efficacy for functional dyspepsia based on routine clinical features: a machine learning study in the framework of predictive, preventive, and personalized medicine

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