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Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening.
Yap, Aaron; Wilkinson, Benjamin; Chen, Eileen; Han, Lydia; Vaghefi, Ehsan; Galloway, Chris; Squirrell, David.
Afiliação
  • Yap A; Department of Ophthalmology, Auckland, New Zealand.
  • Wilkinson B; Department of Ophthalmology, University of Auckland, Auckland, New Zealand.
  • Chen E; School of Optometry and Vision Science, Auckland, New Zealand.
  • Han L; School of Optometry and Vision Science, Auckland, New Zealand.
  • Vaghefi E; School of Optometry and Vision Science, Auckland, New Zealand.
  • Galloway C; Toku Eyes, Auckland, New Zealand.
  • Squirrell D; School of Communication, Journalism and Marketing Massey Business School, New Zealand.
Asia Pac J Ophthalmol (Phila) ; 11(3): 287-293, 2022 May 01.
Article em En | MEDLINE | ID: mdl-35772087
PURPOSE: Artificial intelligence (AI) technology is poised to revolutionize modern delivery of health care services. We set to evaluate the patient perspective of AI use in diabetic retinal screening. DESIGN: Survey. METHODS: Four hundred thirty-eight patients undergoing diabetic retinal screening across New Zealand participated in a survey about their opinion of AI technology in retinal screening. The survey consisted of 13 questions covering topics of awareness, trust, and receptivity toward AI systems. RESULTS: The mean age was 59 years. The majority of participants identified as New Zealand European (50%), followed by Asian (31%), Pacific Islander (10%), and Maori (5%). Whilst 73% of participants were aware of AI, only 58% have heard of it being implemented in health care. Overall, 78% of respondents were comfortable with AI use in their care, with 53% saying they would trust an AI-assisted screening program as much as a health professional. Despite having a higher awareness of AI, younger participants had lower trust in AI systems. A higher proportion of Maori and Pacific participants indicated a preference toward human-led screening. The main perceived benefits of AI included faster diagnostic speeds and greater accuracy. CONCLUSIONS: There is low awareness of clinical AI applications among our participants. Despite this, most are receptive toward the implementation of AI in diabetic eye screening. Overall, there was a strong preference toward continual involvement of clinicians in the screening process. There are key recommendations to enhance the receptivity of the public toward incorporation of AI into retinal screening programs.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Retinopatia Diabética Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Screening_studies Limite: Humans / Middle aged Idioma: En Revista: Asia Pac J Ophthalmol (Phila) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Nova Zelândia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Retinopatia Diabética Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Screening_studies Limite: Humans / Middle aged Idioma: En Revista: Asia Pac J Ophthalmol (Phila) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Nova Zelândia