Predicting dyslipidemia incidence: unleashing machine learning algorithms on Lifestyle Promotion Project data.

Journal: BMC public health
PMID: 38961394

Abstract

BACKGROUND: Dyslipidemia, characterized by variations in plasma lipid profiles, poses a global health threat linked to millions of deaths annually.

Authors

  • Senobar Naderian
    Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Zeinab Nikniaz
    Liver and Gastrointestinal Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Mahdieh Abbasalizad Farhangi
    Department of Community Nutrition, Faculty of Nutrition, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Leila Nikniaz
    Tabriz Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. nikniazleila@gmail.com.
  • Taha Sama-Soltani
    Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran. Samadsoltani@tbzmed.ac.ir.
  • Parisa Rostami
    Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.

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