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  3. Artificial Intelligence in Ophthalmology: Acceptance, Clinical Integration, and Educational Needs in Switzerland.
 

Artificial Intelligence in Ophthalmology: Acceptance, Clinical Integration, and Educational Needs in Switzerland.

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BORIS DOI
10.48620/91404
Publisher DOI
10.3390/jcm14176307
PubMed ID
40944064
Description
Background: Artificial intelligence (AI) can improve efficiency, documentation, and diagnostic quality in ophthalmology. This study examined clinical AI adoption, institutional readiness, perceived utility, trust, ethical concerns, and educational needs among Swiss ophthalmologists and residents. Methods: In May 2025, an anonymous online survey was distributed to board-certified ophthalmologists and residents across Switzerland. The structured questionnaire addressed clinical AI use, institutional infrastructure, perceptions of diagnostic utility, trust, ethical-legal concerns, and educational preparedness. Responses were recorded on five-point Likert scales. Results: Of 106 respondents (mean age 42.4 ± 11.4 years, 48.1% female), 20.8% reported current clinical AI use. Willingness to use AI exceeded 65% across all 10 diagnostic scenarios, but active use remained ≤12.1%. Institutional readiness was low: 6.6% reported AI-related guidelines, 26.4% had access to an institutional AI contact person, and 28.3% received supervisor support (more often among residents). While 80% agreed that AI can support diagnostics, only 12.1% trusted AI recommendations as much as those from colleagues; 87.9% critically reviewed the results, and 93.9% endorsed the use of AI in an assistive but not independently decision-making role. Ethical-legal concerns included unresolved liability (74.8%), informed consent (66.7%), and data protection adequacy (49.5%). Structured AI education was supported by 77.8%, yet only 15.1% felt prepared, and two-thirds (66.7%) indicated they would use AI more with better training. Conclusions: Ophthalmologists and residents in Switzerland express strong interest in the clinical use of AI and recognize its diagnostic potential. Major barriers include insufficient institutional structures, lack of regulatory clarity, and inadequate educational preparation. Addressing these deficits will be essential for responsible AI integration into ophthalmologic practice.
Date of Publication
2025-09-06
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Keyword(s)
Switzerland
•
artificial intelligence (AI)
•
barriers
•
digital affinity
•
ophthalmology
•
training
Language(s)
en
Contributor(s)
Tappeiner, Christophorcid-logo
Clinic of Ophthalmology
Additional Credits
Clinic of Ophthalmology
Series
Journal of Clinical Medicine
Publisher
MDPI
ISSN
2077-0383
Access(Rights)
open.access
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