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Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes.

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Title: Leveraging artificial intelligence and machine learning to accelerate discovery of disease-modifying therapies in type 1 diabetes.
Authors: Shapiro MR; Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA.; Diabetes Institute, University of Florida, Gainesville, FL, USA., Tallon EM; Division of Pediatric Endocrinology and Diabetes, Children's Mercy Kansas City, Kansas City, MO, USA.; Institute for Data Science and Informatics, University of Missouri-Columbia, Columbia, MO, USA.; Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA., Brown ME; Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA.; Diabetes Institute, University of Florida, Gainesville, FL, USA., Posgai AL; Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA.; Diabetes Institute, University of Florida, Gainesville, FL, USA., Clements MA; Division of Pediatric Endocrinology and Diabetes, Children's Mercy Kansas City, Kansas City, MO, USA.; Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA., Brusko TM; Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA. tbrusko@ufl.edu.; Diabetes Institute, University of Florida, Gainesville, FL, USA. tbrusko@ufl.edu.; Department of Pediatrics, College of Medicine, University of Florida, Gainesville, FL, USA. tbrusko@ufl.edu.; Department of Biochemistry and Molecular Biology, College of Medicine, University of Florida, Gainesville, FL, USA. tbrusko@ufl.edu.
Source: Diabetologia [Diabetologia] 2025 Mar; Vol. 68 (3), pp. 477-494. Date of Electronic Publication: 2024 Dec 19.
Publication Type: Journal Article; Review
Journal Info: Publisher: Springer Verlag Country of Publication: Germany NLM ID: 0006777 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-0428 (Electronic) Linking ISSN: 0012186X NLM ISO Abbreviation: Diabetologia Subsets: MEDLINE
Database: MEDLINE Ultimate
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