Mitigation of AI adoption bias through an improved autonomous AI system for diabetic retinal disease

Where adopted, Autonomous artificial Intelligence (AI) for Diabetic Retinal Disease (DRD) resolves longstanding racial, ethnic, and socioeconomic disparities, but AI adoption bias persists. This preregistered trial determined sensitivity and specificity of a previously FDA authorized AI, improved to...

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Veröffentlicht in:NPJ digital medicine Jg. 7; H. 1; S. 369 - 10
Hauptverfasser: Abràmoff, Michael D., Lavin, Philip T., Jakubowski, Julie R., Blodi, Barbara A., Keeys, Mia, Joyce, Cara, Folk, James C.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 19.12.2024
Nature Publishing Group
Nature Portfolio
Schlagworte:
631/114/1305
692/163/2743/137
692/700/139
Artificial intelligence
Bias
Biomedicine
Biotechnology
Cameras
Diabetes
Diabetic retinopathy
Medicine
Medicine & Public Health
Patient safety
Primary care
Technology adoption
ISSN:2398-6352, 2398-6352
Online-Zugang:Volltext
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Zusammenfassung:Where adopted, Autonomous artificial Intelligence (AI) for Diabetic Retinal Disease (DRD) resolves longstanding racial, ethnic, and socioeconomic disparities, but AI adoption bias persists. This preregistered trial determined sensitivity and specificity of a previously FDA authorized AI, improved to compensate for lower contrast and smaller imaged area of a widely adopted, lower cost, handheld fundus camera (RetinaVue700, Baxter Healthcare, Deerfield, IL) to identify DRD in participants with diabetes without known DRD, in primary care. In 626 participants (1252 eyes) 50.8% male, 45.7% Hispanic, 17.3% Black, DRD prevalence was 29.0%, all prespecified non-inferiority endpoints were met and no racial, ethnic or sex bias was identified, against a Wisconsin Reading Center level I prognostic standard using widefield stereoscopic photography and macular Optical Coherence Tomography. Results suggest this improved autonomous AI system can mitigate AI adoption bias, while preserving safety and efficacy, potentially contributing to rapid scaling of health access equity. ClinicalTrials.gov NCT05808699 (3/29/2023).
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ISSN:2398-6352
2398-6352
DOI:10.1038/s41746-024-01389-x