Speech-based recognition and estimating severity of PTSD using machine learning.

Journal: Journal of affective disorders
PMID: 39009320

Abstract

BACKGROUND: Traditional methodologies for diagnosing post-traumatic stress disorder (PTSD) primarily rely on interviews, incurring considerable costs and lacking objective indices. Integrating biomarkers and machine learning techniques into this diagnostic process has the potential to facilitate accurate PTSD assessment by clinicians.

Authors

  • Jiawei Hu
    School of Psychology, Central China Normal University, Key Laboratory of Human Development and Mental Health of Hubei Province, Wuhan 430079, China; Key Laboratory of Adolescent CyberPsychology and Behavior(CCNU), National Intelligent Society Governance Experiment Base (Education), Ministry of Education, Wuhan 430079, China.
  • Chunxiao Zhao
    School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
  • Congrong Shi
    School of Educational Science, Anhui Normal University, Wuhu 241000, China.
  • Ziyi Zhao
    Youth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen, China.
  • Zhihong Ren

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