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Acceptability of artificial intelligence-based retina screening in general population
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 scree...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240537/ https://www.ncbi.nlm.nih.gov/pubmed/35326001 http://dx.doi.org/10.4103/ijo.IJO_1840_21 |
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author | Shah, Payal Mishra, Divyansh Shanmugam, Mahesh Vighnesh, M J Jayaraj, Hariprasad |
author_facet | Shah, Payal Mishra, Divyansh Shanmugam, Mahesh Vighnesh, M J Jayaraj, Hariprasad |
author_sort | Shah, Payal |
collection | PubMed |
description | 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 (REMIDIO™, 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. |
format | Online Article Text |
id | pubmed-9240537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-92405372022-06-30 Acceptability of artificial intelligence-based retina screening in general population Shah, Payal Mishra, Divyansh Shanmugam, Mahesh Vighnesh, M J Jayaraj, Hariprasad Indian J Ophthalmol Featured Article, Artificial Intelligence, Original Article 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 (REMIDIO™, 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. Wolters Kluwer - Medknow 2022-04 2022-03-22 /pmc/articles/PMC9240537/ /pubmed/35326001 http://dx.doi.org/10.4103/ijo.IJO_1840_21 Text en Copyright: © 2022 Indian Journal of Ophthalmology https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Featured Article, Artificial Intelligence, Original Article Shah, Payal Mishra, Divyansh Shanmugam, Mahesh Vighnesh, M J Jayaraj, Hariprasad Acceptability of artificial intelligence-based retina screening in general population |
title | Acceptability of artificial intelligence-based retina screening in general population |
title_full | Acceptability of artificial intelligence-based retina screening in general population |
title_fullStr | Acceptability of artificial intelligence-based retina screening in general population |
title_full_unstemmed | Acceptability of artificial intelligence-based retina screening in general population |
title_short | Acceptability of artificial intelligence-based retina screening in general population |
title_sort | acceptability of artificial intelligence-based retina screening in general population |
topic | Featured Article, Artificial Intelligence, Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240537/ https://www.ncbi.nlm.nih.gov/pubmed/35326001 http://dx.doi.org/10.4103/ijo.IJO_1840_21 |
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