Prediction of health anxiety using resting-state functional near-infrared spectroscopy and machine learning.

Journal: Journal of affective disorders
PMID: 39793619

Abstract

BACKGROUND: The role of cortical networks in health anxiety remain poorly understood. This study aimed to develop a predictive model for health anxiety, using a machine-learning approach based on resting-state functional connectivity (rsFC) with functional near-infrared spectroscopy (fNIRS).

Authors

  • Congrong Shi
    School of Educational Science, Anhui Normal University, Wuhu 241000, China.
  • Xiayu Du
    Key Laboratory of Adolescent Cyberpsychology and Behaviour (Ministry of Education), Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China.
  • Zhihong Ren

Keywords

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