Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study

Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study

Abstract Objective Depression has emerged as a global public health concern with high incidence and disability rates, which are timely imperative to identify and intervene in clinical practice. The objective of this study was to explore the association between heart rate variability (HRV) and depres...

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Bibliographic Details
Main Authors: Min Yang, Huiqin Zhang, Minglan Yu, Yunxuan Xu, Bo Xiang, Xiaopeng Yao
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Psychiatry
Subjects:
Heart rate variability
Depression
Correlation
Machine learning
Predictive model
Online Access:https://doi.org/10.1186/s12888-024-06384-w
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https://doi.org/10.1186/s12888-024-06384-w

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