Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settingsResearch in context

Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settingsResearch in context

Summary: Background: Generalisation of artificial intelligence (AI) models to a new setting is challenging. In this study, we seek to understand the robustness of a dermatology (AI) model and whether it generalises from telemedicine cases to a new setting including both patient-submitted photograph...

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Main Authors: Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong, Preeti Singh, Margaret Ann Smith, Vijaytha Muralidharan, Doris Wong, Rory Sayres, Ayush Jain, Michelle Phung, Nicolas Betancourt, Bradley Fong, Rachna Sahasrabudhe, Khoban Nasim, Alec Eschholz, Basil Mustafa, Jan Freyberg, Terry Spitz, Yossi Matias, Greg S. Corrado, Katherine Chou, Dale R. Webster, Peggy Bui, Yuan Liu, Yun Liu, Justin Ko, Steven Lin
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:EBioMedicine
Subjects:
Artificial intelligence
Generalisation
Dermatology
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396425002105
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http://www.sciencedirect.com/science/article/pii/S2352396425002105

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