Prospective validation of an AI algorithm to identify adult-onset type 1 diabetes misclassification: protocol for a non-interventional multicentre study.
Saved in:
| Title: | Prospective validation of an AI algorithm to identify adult-onset type 1 diabetes misclassification: protocol for a non-interventional multicentre study. |
|---|---|
| Authors: | Brusini I; Applied AI Science, IQVIA, London, UK irene.brusini@iqvia.com., Lee S; Applied AI Science, IQVIA, Wayne, Pennsylvania, USA., Lai A; Applied AI Science, IQVIA, London, UK., Sees A; Applied AI Science, IQVIA, Wayne, Pennsylvania, USA., Hackenberg M; Applied AI Science, IQVIA, Wayne, Pennsylvania, USA., Liptak G; HealthShare Exchange (HSX), Philadelphia, Pennsylvania, USA., Rao AD; Section of Endocrinology, Diabetes and Metabolism, Temple University, Philadelphia, Pennsylvania, USA.; Center for Metabolic Disease Research, Temple University, Philadelphia, Pennsylvania, USA., Anastasopoulou C; Endocrinology Department, Jefferson Einstein Medical Center, Philadelphia, Pennsylvania, USA., Leavitt N; Applied AI Science, IQVIA, Wayne, Pennsylvania, USA. |
| Source: | BMJ open [BMJ Open] 2026 Jun 10; Vol. 16 (6), pp. e112819. Date of Electronic Publication: 2026 Jun 10. |
| Publication Type: | Journal Article; Validation Study |
| Journal Info: | Publisher: BMJ Publishing Group Ltd Country of Publication: England NLM ID: 101552874 Publication Model: Electronic Cited Medium: Internet ISSN: 2044-6055 (Electronic) Linking ISSN: 20446055 NLM ISO Abbreviation: BMJ Open Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2044-6055 |
|---|---|
| DOI: | 10.1136/bmjopen-2025-112819 |
