MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach.

Journal: Journal of affective disorders
PMID: 38788856

Abstract

BACKGROUND: Major depressive disorder (MDD) is notably underdiagnosed and undertreated due to its complex nature and subjective diagnostic methods. Biomarker identification would help provide a clearer understanding of MDD aetiology. Although machine learning (ML) has been implemented in previous studies to study the alteration of microRNA (miRNA) levels in MDD cases, clinical translation has not been feasible due to the lack of interpretability (i.e. too many miRNAs for consideration) and stability.

Authors

  • Yee Ling Chan
    Centre for Intelligent Signal and Imaging Research (CISIR), Universiti Teknologi PETRONAS (UTP), Bandar Seri Iskandar 32610, Perak, Malaysia.
  • Cyrus S H Ho
    Department of Psychological Medicine, National University Hospital, Singapore 119074, Singapore. cyrushosh@gmail.com.
  • Gabrielle W N Tay
    Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117543, Singapore.
  • Trevor W K Tan
    Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117543, Singapore; Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117543, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore; N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore 117456, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore 119077, Singapore.
  • Tong Boon Tang
    Centre of Intelligent Signal and Imaging Research, Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, 32610, Bandar Seri Iskandar, Perak, Malaysia. tongboon.tang@petronas.com.my.

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