Artificial intelligence–assisted detection of diabetic retinopathy on digital fundus images: concepts and applications in the National Health Service

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Diabetic retinopathy (DR), one of the most devastating manifestations of diabetes, is a leading cause of blindness among working-age adults. World Health Organization predicts the prevalence of diabetes to increase substantially in the future, leading to an increasing pressure on public health services. In the context of smart healthcare, DR screening has been widely adopted by utilizing fundus imaging with manual input. In this chapter, we review the potential of artificial intelligence enabled automated screening for the detection and classification of DR in the context of the National Health Service. We propose an integrated multimodal approach to enable the combination of manual (through human graders) and automated DR screening. Furthermore, we discuss how this multimodal approach can be enhanced by the integration of additional modalities such as optical coherence tomography. Artificial intelligence in that setting can complement and upskill human graders by acting in an assistive way rather than replacing their role.
Original languageEnglish
Title of host publicationInnovation in Health Informatics
Subtitle of host publicationA Smart Healthcare Primer
PublisherElsevier
Chapter11
Pages261-278
Number of pages18
ISBN (Print)9780128190432
DOIs
Publication statusPublished - 2020

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