Acceptability of artificial intelligence-based retina screening in general population

Autor: PayalShah, DivyanshMishra, MaheshShanmugam, M J Vighnesh, HariprasadJayaraj
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Indian Journal of Ophthalmology, Vol 70, Iss 4, Pp 1140-1144 (2022)
Druh dokumentu: article
ISSN: 0301-4738
1998-3689
DOI: 10.4103/ijo.IJO_1840_21
Popis: Purpose: A deep learning system (DLS) using artificial intelligence (AI) is emerging as a very promising technology in the future of healthcare diagnostics. While the concept of telehealth is emerging in every field of medicine, AI assistance in diagnosis can become a great tool for successful screening in telemedicine and teleophthalmology. The aim of our study was to assess the acceptability of AI-based retina screening. Methods: This was a prospective non-randomized study performed in the outpatient department of a tertiary eye care hospital. Patients older than 18 years who came for a regular eye check-up or a routine retina screening were recruited in the study. Fundus images of the posterior pole were captured on fundus on a phone camera (REMIDIOTM, India) with a built-in AI software (Netra.AI) that can identify normal versus abnormal retina. The patients were then given an 8-point questionnaire to assess their acceptance and willingness toward AI-based screening. We recruited 104 participants. Results: We found that 90.4% were willing for an AI-based fundus screening; 96.2% were satisfied with AI-based screening. Patients with diabetes (P = 0.03) and the male population (P = 0.029) were more satisfied with the AI-based screening. The majority (i.e., 97.1%) felt that AI-based screening gave them a better understanding of their eye condition and 37.5% felt that AI-based retina screening prior to a doctor's visit can help in routine screening. Conclusion: Considering the current COVID-19 pandemic situation across the globe, this study highlights the importance of AI-based telescreening and positive patient approach toward this technology.
Databáze: Directory of Open Access Journals
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