Integrating Heart Rate Variability Improves Machine Learning-based Prediction of Panic Disorder Symptom Severity.

ABSTRACT:

Objective

The association between panic disorder (PD) and heart rate variability (HRV) has long been studied with a focus on the imbalance of the autonomic nervous system. This study aims to demonstrate the predictive capability of HRV in determining PD severity using machine learning.

Methods

Psychometric scales and various HRV components were measured from 507 PD patients who were recruited. We designed three experiments with different sets of input features for comparison. The input features of each experiment were 1) both psychometric scales and HRV together (ExSH), or 2) only the scales (ExS), or 3) only the HRV components. In each experiment, nine machine learning models were used to predict the Panic Disorder Severity Scale. We compared the predictive capability of th

SUBMITTER: Lee JG 

PROVIDER: S-EPMC12264673 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature