A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation.

ABSTRACT:

Background

Syndrome differentiation in traditional Chinese medicine (TCM) is an ancient principle that guides disease diagnosis and treatment. Among these, the cold and hot syndromes play a crucial role in identifying the nature of the disease and guiding the treatment of viral pneumonia. However, differentiating between cold and hot syndromes is often considered esoteric. Machine learning offers a promising avenue for clinicians to identify these syndromes more accurately, thereby supporting more informed clinical decision-making in the treatment.

Objective

This study aims to construct a diagnostic model for differentiating cold and hot syndromes in viral pneumonia by integrating TCM and modern medical features using machine learning methods.

Methods

The application

SUBMITTER: Jin X 

PROVIDER: S-EPMC12286567 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature