Deploying machine learning models in clinical settings: a real-world feasibility analysis for a model identifying adult-onset type 1 diabetes initially classified as type 2.
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| Title: | Deploying machine learning models in clinical settings: a real-world feasibility analysis for a model identifying adult-onset type 1 diabetes initially classified as type 2. |
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| Authors: | Brusini I; AI for Healthcare & MedTech, IQVIA, London W2 1AF, United Kingdom., Lee S; AI for Healthcare & MedTech, IQVIA, Wayne, PA 19087, United States., Hollingsworth J; AI for Healthcare & MedTech, IQVIA, Wayne, PA 19087, United States., Sees A; AI for Healthcare & MedTech, IQVIA, Wayne, PA 19087, United States., Hackenberg M; AI for Healthcare & MedTech, IQVIA, Wayne, PA 19087, United States., Scherpbier H; HealthShare Exchange (HSX), Philadelphia, PA 19106, United States., López-Díez R; Breakthrough T1D (Formerly JDRF International), New York, NY 10281, United States., Leavitt N; AI for Healthcare & MedTech, IQVIA, Wayne, PA 19087, United States. |
| Source: | JAMIA open [JAMIA Open] 2025 Oct 26; Vol. 8 (5), pp. ooaf133. Date of Electronic Publication: 2025 Oct 26 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press on behalf of the American Medical Informatics Association Country of Publication: United States NLM ID: 101730643 Publication Model: eCollection Cited Medium: Internet ISSN: 2574-2531 (Electronic) Linking ISSN: 25742531 NLM ISO Abbreviation: JAMIA Open Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2574-2531 |
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| DOI: | 10.1093/jamiaopen/ooaf133 |
