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

ABSTRACT:

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 identify the FD patients who were appropriate to acupuncture treatment.

Methods

A total of 745 FD patients were collected from two clinical trials. All the patients received a 4-week ac

SUBMITTER: Yin T 

PROVIDER: S-EPMC8897529 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature