Work

Targeting weight loss interventions to reduce cardiovascular complications of type 2 diabetes: a machine learning-based post-hoc analysis of heterogeneous treatment effects in the Look AHEAD trial

Year: 2017

Type: article

Source: The Lancet Diabetes & Endocrinology

DOI: 10.1016/s2213-8587(17)30176-6

Authors: Aaron Baum, Joseph Scarpa, Emilie Bruzelius, Ronald Tamler, Sanjay Basu, James Faghmous

Institutions: Icahn School of Medicine at Mount Sinai, Columbia University, Stanford Medicine, Stanford University

Language: English

Topic: Diabetes, Cardiovascular Risks, and Lipoproteins

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Science Foundation, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Institute on Minority Health and Health Disparities

Awards: G1421216546, G208841273, Cohort filtering models to identify social program effects on health disparities, Studying social factors in sodium consumption to reduce hypertension disparities, CRII: III: Spatio-Temporal Data Mining to Learn From Unlabeled Climate Data, Probing networks underlying sleep and stress with multiscale data, G898467768, G9000052644

OpenAlex ID: W2734626658

FWCI: 9.511

Cites: 28

Cited by: 120

Related to: 10