Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies.

Journal: BMC medical informatics and decision making
Published Date: May 27, 2024

Abstract

OBJECTIVE: Suicide is a complex and multifactorial public health problem. Understanding and addressing the various factors associated with suicide is crucial for prevention and intervention efforts. Machine learning (ML) could enhance the prediction of suicide attempts.

Authors

  • Houriyeh Ehtemam
    School of Engineering and the Built Environment, Anglia Ruskin University, Chelmsford, UK.
  • Shabnam Sadeghi Esfahlani
    School of Engineering and the Built Environment, Anglia Ruskin University, Chelmsford, UK.
  • Alireza Sanaei
    School of Engineering and the Built Environment, Anglia Ruskin University, Chelmsford, UK.
  • Mohammad Mehdi Ghaemi
    Health Services Management Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. academic.businessmail@gmail.com.
  • Sadrieh Hajesmaeel-Gohari
    Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Rohaneh Rahimisadegh
    Health Services Management Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Kambiz Bahaadinbeigy
    Medical Informatics Research Center, Institute for Future Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
  • Fahimeh Ghasemian
    Department of Computer Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran.
  • Hassan Shirvani
    School of Engineering and the Built Environment, Anglia Ruskin University, Chelmsford, UK.

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