A machine learning model to predict therapeutic inertia in type 2 diabetes using electronic health record data.

Cassidi C McDanielW-H Lo-CiganicJ HuangC Chou

Published in: Journal of endocrinological investigation (2023)

Using EHRs of patients with type 2 diabetes from a large state, machine learning predicted therapeutic inertia (prevalence = 40%). The model's ability to predict patients at high risk of therapeutic inertia is clinically applicable to diabetes care.

Keyphrases

electronic health record
machine learning
type diabetes
big data
clinical decision support
artificial intelligence
risk factors
cardiovascular disease
deep learning
glycemic control