Artificial intelligence-enabled obesity prediction: A systematic review of cohort data analysis.

Journal: International journal of medical informatics
PMID: 39870016

Abstract

BACKGROUND: Obesity, now the fifth leading global cause of death, has seen a dramatic rise in prevalence over the last forty years. It significantly increases the risk of diseases such as type 2 diabetes and cardiovascular disease. Early identification of obesity risk allows for preventative actions against obesity-related factors. Despite the existence of AI-based predictive models, developing a comprehensive obesity screening tool requires extensive cohort data.

Authors

  • Sharareh Rostam Niakan Kalhori
    Department of Health Information Management and Medical Informatics School of Allied Medical Sciences Tehran University of Medical Sciences Tehran Iran; Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School Braunschweig Germany. Electronic address: Sh-rniakank@tums.ac.ir.
  • Farid Najafi
    Research Center for Environmental Determinants of Health, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran.
  • Hajar Hasannejadasl
    Department of Health Information Management and Medical Informatics School of Allied Medical Sciences Tehran University of Medical Sciences Tehran Iran.
  • Soroush Heydari
    Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

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