DIABETIA
Longitudinal study for the development of predictive models for chronic complications of type 2 diabetes mellitus
Description
DiabetIA is a digital health research initiative focused on developing machine learning predictive models to anticipate chronic complications in patients with Type 2 Diabetes Mellitus. The project combines advanced data science with clinical information governance to advance precision medicine in Mexico.
Bioethics
- Reviewing committees
- National Research Committee and National Research Ethics Committee (IMSS)
- Protocol registration ID
- PI-2018-1671
Funding
- Source
- CONACYT (FORDECyT / ProNacEs)
- Program
- Data Science and Health Call (Registry 10410)
Collaborators
AG
Dra. Anel Gómez García
CIBIMI IMSS
Principal Investigator
Dr. Arturo López Pineda
ENES Morelia, UNAM / Amphora Health
Co-InvestigatorCA
Dr. Cleto Alvarez Aguilar
Faculty of Medicine, UMSNH
Co-InvestigatorKM
Dra. Karina M. Figueroa Mora
FISMAT UMSNH
Co-InvestigatorMG
Dra. Marisol Flores Garrido
ENES Morelia, UNAM
Co-InvestigatorLV
Dr. Luis Miguel García Velázquez
ENES Morelia, UNAM
Co-InvestigatorSubprojects
Flagship Project to Describe the Repository
ActiveDiabetes Complications Modeling
ActivePublished Articles
- DiabetIA: Building Machine Learning Models for Type 2 Diabetes Complications · medRxiv preprint, 2023