Designing a machine learning model for predicting cardiovascular events using the triglyceride-glucose index: a cohort study
This study highlights the potential benefits of incorporating the TyG index into traditional CVD risk prediction models to enhance accuracy and applicability, especially in developing countries.
Authors
- M. Emadzadeh
- Bahram Shahri
- Vahid Mahdavizadeh
- Armin Doostparast (ORCID: https://orcid.org/0009-0000-2903-7649)
- Farzam Kamrani (ORCID: https://orcid.org/0009-0001-2460-4218)
- A Heidari-Bakavoli
- Hedieh Alimi
- Negin Sarvari
- Mohsen Moohebati
- Pegah moosavi
- Susan Darroudi
- Majid Ghayour-Mobarhan
- Parsa Seyed Hosseini
- Habibollah Esmaily
Institutions
- Mashhad University of Medical Sciences (IR)
- Ghaem Hospital (IR)
Publication Details
- Journal
- Computers in Biology and Medicine
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1016/j.compbiomed.2026.111556
- Primary Topic
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Type
- article
- Field-Weighted Citation Impact
- 0.00