Artificial Intelligence Bias and Ethics in Retinal Imaging
Author:
Affiliation:
1. Singapore National Eye Center, Singapore Eye Research Institute, Singapore, Singapore
2. Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
Publisher
American Medical Association (AMA)
Subject
Ophthalmology
Link
https://jamanetwork.com/journals/jamaophthalmology/articlepdf/2804445/jamaophthalmology_tan_2023_ic_230019_1686235860.2301.pdf
Reference8 articles.
1. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs.;Gulshan;JAMA,2016
2. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes.;Ting;JAMA,2017
3. Nonhuman “authors” and implications for the integrity of scientific publication and medical knowledge.;Flanagin;JAMA,2023
4. AI can be sexist and racist: it’s time to make it fair.;Zou;Nature,2018
5. Addressing artificial intelligence bias in retinal diagnostics.;Burlina;Transl Vis Sci Technol,2021
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