Published on in Vol 7, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27304, first published .
Using Machine Learning Techniques to Predict Factors Contributing to the Incidence of Metabolic Syndrome in Tehran: Cohort Study

Using Machine Learning Techniques to Predict Factors Contributing to the Incidence of Metabolic Syndrome in Tehran: Cohort Study

Using Machine Learning Techniques to Predict Factors Contributing to the Incidence of Metabolic Syndrome in Tehran: Cohort Study

Firoozeh Hosseini-Esfahani   1 * , PhD ;   Behnaz Alafchi   2 * , PhD ;   Zahra Cheraghi   3, 4 * , PhD ;   Amin Doosti-Irani   4, 5 * , PhD ;   Parvin Mirmiran   1 * , PhD ;   Davood Khalili   6, 7 , MD, PhD ;   Fereidoun Azizi   6 , MD

1 Department of Clinical Nutrition and Dietetics, Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Science, Tehran, Iran

2 Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran

3 Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran

4 Department of Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran

5 Health and Research Center for Health Sciences, Hamadan University of Medical Sciences, Hamadan, Iran

6 Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

7 Department of Biostatistics and Epidemiology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

*these authors contributed equally

Corresponding Author:

  • Zahra Cheraghi, PhD
  • Modeling of Noncommunicable Diseases Research Center
  • Hamadan University of Medical Sciences
  • Shahid Fahmideh Ave. Hamadan, Islamic Republic of Iran.
  • Hamadan, 65157835129
  • Iran
  • Phone: 98 9183177990
  • Fax: 98 81338380509
  • Email: cheraghiz@ymail.com