Clinical and Experimental Dermatology · 2021 · 35 citations · 6 references
MedicineDermatologyOncologyArtificial IntelligenceCutaneous OncologyMachine LearningSkin CareSkin ExaminationDiagnostic Accuracy StudiesSkin Cancer DetectionTechnology Acceptance Of Ai
BACKGROUND: Convolutional neural networks (artificial intelligence, AI) are rapidly appearing within the field of dermatology, with diagnostic accuracy matching that of dermatologists. As technologies become available for use by both the health professionals and the general public, their uptake in healthcare will become more acceptable. National Health Service England recognizes the potential of AI for healthcare but emphasizes that patient-centred care should be at the forefront of these technological advancements. AIM: To obtain opinions of patients on the use of AI in a dermatology setting, when aiding the diagnosis of skin cancers. METHODS: A cross-sectional 14-point questionnaire was handed out to patients attending dermatology outpatient skin cancer clinics in two UK hospitals, between March and August 2018. RESULTS: In total, 603 patient questionnaires were completed. Nearly half (47%; n = 282) of respondents were not concerned if AI technology was used by a skin specialist to aid skin cancer diagnosis. However, the majority (81%; n = 491) of respondents, considered it important for a dermatologist to examine and confirm a diagnosis and to be present for discussion of a cancer diagnosis. CONCLUSION: Although the majority of respondents were not reluctant about the use of AI for skin cancer diagnosis, respondents still considered it important that dermatologists are involved in the diagnosis and/or confirmation of skin cancer. Furthermore, the study results demonstrate that personal interaction with a clinician is important. This is in keeping with proposals that AI be used as an adjunctive technology to increase accuracy of skin cancer diagnoses, but not as a substitute for a dermatologist.
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