Predicting new-onset stroke with machine learning: development of a model integrating traditional Chinese and western medicine.

ABSTRACT:

Introduction

The integration of traditional Chinese medicine (TCM) and Western medicine has demonstrated effectiveness in the primary prevention of stroke. Therefore, our study aims to utilize TCM syndromes alongside conventional risk factors as predictive variables to construct a machine learning model for assessing the risk of new-onset stroke.

Methods

We conducted a ten-year follow-up study encompassing 4,511 participants from multiple Chinese community hospitals. The dependent variable was the occurrence of the new-onset stroke, while independent variables included age, gender, systolic blood pressure (SBP), diabetes, blood lipids, carotid atherosclerosis, smoking status, and TCM syndromes. We developed the models using XGBoost in conjunction with SHapley Additive exPlan

SUBMITTER: Wang L 

PROVIDER: S-EPMC11885310 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature