Artificial intelligence survival models for identifying relevant risk factors for incident diabetes in Azar cohort population

Artificial intelligence survival models for identifying relevant risk factors for incident diabetes in Azar cohort population

Background: This study aimed to identify some risk factors associated with time to diabetes type II events using artificial intelligence (AI) survival models (SM) in a population cohort from East Azerbaijan, Iran. Methods: Data from Azar-Cohort spanning from 2014 to 2020 was analyzed using the rando...

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Bibliographic Details
Main Authors: Neda Gilani, Mohammadhossein Somi, Farzaneh Hamidi, Pasqualina Santaguida, Elnaz Faramarzi, Reza Arabi Belaghi
Format: Article
Language:English
Published: Tabriz University of Medical Sciences 2025-05-01
Series:Health Promotion Perspectives
Subjects:
cohort study
diabetes mellitus
incidence
random forest
survival analysis
Online Access:https://hpp.tbzmed.ac.ir/PDF/hpp-15-82.pdf
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https://hpp.tbzmed.ac.ir/PDF/hpp-15-82.pdf

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