Trustworthy Evaluation of Clinical AI for Analysis of Medical Images in Diverse Populations-Reference-Cited by-同舟云学术

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Trustworthy Evaluation of Clinical AI for Analysis of Medical Images in Diverse Populations

Published:2024-08-22 Issue:9 Volume:1 Page:
ISSN:2836-9386
Container-title:NEJM AI
language:en
Short-container-title:NEJM AI

Author:

Fajtl Jiri¹^ORCID,Welikala Roshan A.¹^ORCID,Barman Sarah¹^ORCID,Chambers Ryan²^ORCID,Bolter Louis²^ORCID,Anderson John²^ORCID,Olvera-Barrios Abraham³^ORCID,Shakespeare Royce⁴^ORCID,Egan Catherine³^ORCID,Owen Christopher G.⁴^ORCID,Tufail Adnan³^ORCID,Rudnicka Alicja R.⁴^ORCID

Affiliation:

1. School of Computer Science and Mathematics, Kingston University, London

2. Diabetes and Endocrinology, Homerton Healthcare NHS Foundation Trust, London

3. NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London

4. Population Health Research Institute, St. George’s University of London, London

Publisher

Massachusetts Medical Society

Reference31 articles.

1. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045

2. Estimating the current and future costs of Type 1 and Type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs

3. Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application

4. Diabetic retinopathy

5. A comparison of the causes of blindness certifications in England and Wales in working age adults (16–64 years), 1999–2000 with 2009–2010

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