Xie, Y;
Gunasekeran, DV;
Balaskas, K;
Keane, PA;
Sim, DA;
Bachmann, LM;
Macrae, C;
(2020)
Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening.
Translational Vision Science and Technology
, 9
(2)
, Article 22. 10.1167/tvst.9.2.22.
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Abstract
Systematic screening for diabetic retinopathy (DR) has been widely recommended for early detection in patients with diabetes to address preventable vision loss. However, substantial manpower and financial resources are required to deploy opportunistic screening and transition to systematic DR screening programs. The advent of artificial intelligence (AI) technologies may improve access and reduce the financial burden for DR screening while maintaining comparable or enhanced clinical effectiveness. To deploy an AI-based DR screening program in a real-world setting, it is imperative that health economic assessment (HEA) and patient safety analyses are conducted to guide appropriate allocation of resources and design safe, reliable systems. Few studies published to date include these considerations when integrating AI-based solutions into DR screening programs. In this article, we provide an overview of the current state-of-the-art of AI technology (focusing on deep learning systems), followed by an appraisal of existing literature on the applications of AI in ophthalmology. We also discuss practical considerations that drive the development of a successful DR screening program, such as the implications of false-positive or false-negative results and image gradeability. Finally, we examine different plausible methods for HEA and safety analyses that can be used to assess concerns regarding AI-based screening.
| Type: | Article |
|---|---|
| Title: | Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1167/tvst.9.2.22 |
| Publisher version: | https://doi.org/10.1167/tvst.9.2.22 |
| Language: | English |
| Additional information: | Copyright © 2020 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0). |
| Keywords: | artificial intelligence; ocular imaging; diabetic retinopathy; machine learning; deep learning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10114733 |
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