Multimodal artificial intelligence for retinal detachment diagnosis using fundus imaging and patient questionnaires.

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Bibliographic Details
Title: Multimodal artificial intelligence for retinal detachment diagnosis using fundus imaging and patient questionnaires.
Authors: Yonemaru N; Technology Laboratory, Cresco Ltd, Minato-ku, Tokyo, Japan n-yonemaru@cresco.co.jp., Tabuchi H; Department of Ophthalmology, Tsukazaki Hosital, Himeji, Hyogo, Japan.; Department of Technology and Design Thinking for Medicine, Hiroshima University, Hiroshima, Hiroshima, Japan.; Department of Ophthalmology, Hyogo Medical University, Nishinomiya, Hyogo, Japan., Deguchi H; Department of Ophthalmology, Tsukazaki Hosital, Himeji, Hyogo, Japan., Omi Y; Department of Ophthalmology, Tsukazaki Hosital, Himeji, Hyogo, Japan., Tanabe M; Department of Ophthalmology, Tsukazaki Hosital, Himeji, Hyogo, Japan., Ishitobi N; Department of Ophthalmology, Tsukazaki Hosital, Himeji, Hyogo, Japan., Maruyama H; Technology Laboratory, Cresco Ltd, Minato-ku, Tokyo, Japan., Ayatsuka Y; Technology Laboratory, Cresco Ltd, Minato-ku, Tokyo, Japan.
Source: The British journal of ophthalmology [Br J Ophthalmol] 2026 Apr 22; Vol. 110 (5), pp. 586-591. Date of Electronic Publication: 2026 Apr 22.
Publication Type: Journal Article
Journal Info: Publisher: BMJ Pub. Group Country of Publication: England NLM ID: 0421041 Publication Model: Electronic Cited Medium: Internet ISSN: 1468-2079 (Electronic) Linking ISSN: 00071161 NLM ISO Abbreviation: Br J Ophthalmol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1468-2079
DOI:10.1136/bjo-2025-327506