Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals

Author
M. Mizani
A. Dashtban
L. Pasea
Q. Zeng
K. Khunti
J. Valabhji
J. Mamza
H. Gao
T. Morris
A. Banerjee
Keywords
Humans
*Diabetes Mellitus, Type 2/epidemiology/drug therapy
*Electronic Health Records/statistics & numerical data
Female
Male
*Machine Learning
Middle Aged
Prognosis
Aged
Adult
Hypoglycemic Agents/therapeutic use
Incidence
Follow-Up Studies
diabetes mellitus, type 2
Electronic Health Records
epidemiology
Informatics
biopharmaceutical company, and declare stock and stock options. AB has received
research funding from AstraZeneca. KK has acted as a consultant, speaker or
received grants for investigator-initiated studies for AstraZeneca, Bayer,
Novartis, Novo Nordisk, Sanofi-Aventis, Lilly and Merck Sharp & Dohme, Boehringer
Ingelheim, Oramed Pharmaceuticals, Roche and Applied Therapeutics.
Year of Publication
2024
Journal
BMJ Open Diabetes Res Care
Volume
12
ISBN Number
2052-4897
Accession Number
38834334
DOI
10.1136/bmjdrc-2024-004191