| Autor: |
Josie Carmichael, Enrico Costanza, Ann Blandford, Robbert Struyven, Pearse A. Keane, Konstantinos Balaskas |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-024-55410-0 |
| Popis: |
Abstract Artificial intelligence (AI) has great potential in ophthalmology. We investigated how ambiguous outputs from an AI diagnostic support system (AI-DSS) affected diagnostic responses from optometrists when assessing cases of suspected retinal disease. Thirty optometrists (15 more experienced, 15 less) assessed 30 clinical cases. For ten, participants saw an optical coherence tomography (OCT) scan, basic clinical information and retinal photography (‘no AI’). For another ten, they were also given AI-generated OCT-based probabilistic diagnoses (‘AI diagnosis’); and for ten, both AI-diagnosis and AI-generated OCT segmentations (‘AI diagnosis + segmentation’) were provided. Cases were matched across the three types of presentation and were selected to include 40% ambiguous and 20% incorrect AI outputs. Optometrist diagnostic agreement with the predefined reference standard was lowest for ‘AI diagnosis + segmentation’ (204/300, 68%) compared to ‘AI diagnosis’ (224/300, 75% p = 0.010), and ‘no Al’ (242/300, 81%, p = |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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