Heat syndrome types prediction of traditional Chinese medicine in acute ischemic stroke through deep learning: a pilot study.

ABSTRACT: Integrating Chinese medicine and biomedicine for treating acute ischemic stroke (AIS) presents a promising strategy. Accurately predicting Traditional Chinese Medicine (TCM) heat syndrome types in AIS patients is crucial for guiding appropriate medication use within this combined treatment strategy. In this study, a clinical cohort including TCM syndromes, laboratory markers, and baseline assessments, were collected from 193 AIS patients. We developed a deep learning method with Convolutional Neural Networks (CNNs) to predict heat syndrome types in AIS patients by integrating TCM pattern characteristics and laboratory indicators. Feature importance was assessed using SHapley Additive exPlanations (SHAP) and permutation importance, and partial dependence plots (PDP) were used to explore the

SUBMITTER: Yu X 

PROVIDER: S-EPMC12358418 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature