Deployment of Artificial Intelligence in Real-World Practice: Opportunity and Challenge.

Asia-Pacific Journal of Ophthalmology
Mingguang HeZachary Tan

Abstract

Artificial intelligence has rapidly evolved from the experimental phase to the implementation phase in many image-driven clinical disciplines, including ophthalmology. A combination of the increasing availability of large datasets and computing power with revolutionary progress in deep learning has created unprecedented opportunities for major breakthrough improvements in the performance and accuracy of automated diagnoses that primarily focus on image recognition and feature detection. Such an automated disease classification would significantly improve the accessibility, efficiency, and cost-effectiveness of eye care systems where it is less dependent on human input, potentially enabling diagnosis to be cheaper, quicker, and more consistent. Although this technology will have a profound impact on clinical flow and practice patterns sooner or later, translating such a technology into clinical practice is challenging and requires similar levels of accountability and effectiveness as any new medication or medical device due to the potential problems of bias, and ethical, medical, and legal issues that might arise. The objective of this review is to summarize the opportunities and challenges of this transition and to facilitate t...Continue Reading

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Citations

Nov 13, 2020·Eye·Timothy Y Y Lai
May 23, 2021·BMC Ophthalmology·William Greig MitchellLeo Anthony Celi
Aug 21, 2021·Ophthalmology·Tien-En TanDaniel Shu Wei Ting
Aug 13, 2021·Asia-Pacific Journal of Ophthalmology·Rachel Marjorie Wei Wen TsengYih-Chung Tham
Oct 16, 2021·Journal of Medical Internet Research·Luisa PumplunPeter Buxmann

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