Artificial intelligence in diabetic retinopathy: Insights from a meta-analysis of deep learning

Tahmina Nasrin Poly, Md Mohaimenul Islam, Hsuan Chia Yang, Phung Anh Nguyen, Chieh Chen Wu, Yu Chuan Lia

研究成果: 書貢獻/報告類型會議貢獻

4 引文 斯高帕斯(Scopus)

摘要

The demand for AI to improve patients outcome has been increased; we, therefore, aim to establish the diagnostic values of AI in diabetic retinopathy by pooling the published studies of deep learning on this subject. A total of eight studies included which evaluated deep learning in a total of 706,922 retinal images. The overall pooled area under receiver operating curve (AUROC) was 98.93% (95%CI:98.37%-99.49%). However, the overall pooled sensitivity and specificity for detecting referable diabetic retinopathy (RDR) was 74% (95% CI: 73%-74%), and 95% (95% CI: 95%-95%). The findings of this study show that deep learning had high sensitivity and specificity for identifying diabetic retinopathy.
原文英語
主出版物標題MEDINFO 2019
主出版物子標題Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
編輯Brigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
發行者IOS Press
頁面1556-1557
頁數2
ISBN(電子)9781643680026
DOIs
出版狀態已發佈 - 八月 21 2019
對外發佈
事件17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, 法国
持續時間: 八月 25 2019八月 30 2019

出版系列

名字Studies in Health Technology and Informatics
264
ISSN(列印)0926-9630
ISSN(電子)1879-8365

會議

會議17th World Congress on Medical and Health Informatics, MEDINFO 2019
國家/地區法国
城市Lyon
期間8/25/198/30/19

ASJC Scopus subject areas

  • 生物醫學工程
  • 健康資訊學
  • 健康資訊管理

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