The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading

The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading

Abstract We developed an AI system capable of automatically classifying anterior eye images as either normal or indicative of corneal diseases. This study aims to investigate the influence of AI’s misleading guidance on ophthalmologists’ responses. This cross-sectional study included 30 cases each o...

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Bibliographic Details
Main Authors: Hiroki Maehara, Yuta Ueno, Takefumi Yamaguchi, Yoshiyuki Kitaguchi, Dai Miyazaki, Ryohei Nejima, Takenori Inomata, Naoko Kato, Tai-ichiro Chikama, Jun Ominato, Tatsuya Yunoki, Kinya Tsubota, Masahiro Oda, Manabu Suzutani, Tetsuju Sekiryu, Tetsuro Oshika
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
AI
Artificial intelligence
Ocular surface
Misleading AI guidance
AI assist
Online Access:https://doi.org/10.1038/s41598-025-85827-0
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