This paper is in the following e-collection/theme issue:

Diabetes Prevention (96) Decision Support for Health Professionals (1323) Prevention and Health Promotion (1111) Machine Learning (1685)

Published on in Vol 8 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44018, first published .
Prediction of Weight Loss to Decrease the Risk for Type 2 Diabetes Using Multidimensional Data in Filipino Americans: Secondary Analysis

Prediction of Weight Loss to Decrease the Risk for Type 2 Diabetes Using Multidimensional Data in Filipino Americans: Secondary Analysis

Prediction of Weight Loss to Decrease the Risk for Type 2 Diabetes Using Multidimensional Data in Filipino Americans: Secondary Analysis

Authors of this article:

Lisa Chang1, 2 Author Orcid Image ;   Yoshimi Fukuoka1 Author Orcid Image ;   Bradley E Aouizerat3, 4 Author Orcid Image ;   Li Zhang5, 6 Author Orcid Image ;   Elena Flowers1, 7 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Sinha R, Das J, Mazumder P, Aggarwal Y. NONLINEAR HEART RATE VARIABILITY FEATURES IN DEPICTING THE EFFICACY OF RUTIN UNDER STREPTOZOTOCIN-INDUCED DIABETES MODEL WITH SUPPORT VECTOR MACHINE. Biomedical Engineering: Applications, Basis and Communications 2023;35(04) View
  2. Zimmermann S, Roomp K, Meyer H, Mathew A, Struck M, Blüher M, Martin H, Keller M, Landgraf K, Körner A, Hoffmann A, Böttcher Y, Biemann K, Ghosh A, Wolfrum C, Noé F, Isermann B, Schneider J, Biemann R. Association of Lifestyle‐Induced Weight Loss With Gene Expression in Subcutaneous Adipose Tissue in Metabolic Syndrome. Journal of Diabetes 2025;17(4) View