{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T14:58:12Z","timestamp":1784041092804,"version":"3.55.0"},"reference-count":167,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T00:00:00Z","timestamp":1662595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Deep learning (DL) enables the creation of computational models comprising multiple processing layers that learn data representations at multiple levels of abstraction. In the recent past, the use of deep learning has been proliferating, yielding promising results in applications across a growing number of fields, most notably in image processing, medical image analysis, data analysis, and bioinformatics. DL algorithms have also had a significant positive impact through yielding improvements in screening, recognition, segmentation, prediction, and classification applications across different domains of healthcare, such as those concerning the abdomen, cardiac, pathology, and retina. Given the extensive body of recent scientific contributions in this discipline, a comprehensive review of deep learning developments in the domain of diabetic retinopathy (DR) analysis, viz., screening, segmentation, prediction, classification, and validation, is presented here. A critical analysis of the relevant reported techniques is carried out, and the associated advantages and limitations highlighted, culminating in the identification of research gaps and future challenges that help to inform the research community to develop more efficient, robust, and accurate DL models for the various challenges in the monitoring and diagnosis of DR.<\/jats:p>","DOI":"10.3390\/s22186780","type":"journal-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T04:18:32Z","timestamp":1662610712000},"page":"6780","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":89,"title":["Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions"],"prefix":"10.3390","volume":"22","author":[{"given":"Muhammad Waqas","family":"Nadeem","sequence":"first","affiliation":[{"name":"Faculty of Information and Communication Technology (FICT), Universiti Tunku Abdul Rahman (UTAR), Kampar 31900, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2416-5777","authenticated-orcid":false,"given":"Hock Guan","family":"Goh","sequence":"additional","affiliation":[{"name":"Faculty of Information and Communication Technology (FICT), Universiti Tunku Abdul Rahman (UTAR), Kampar 31900, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1288-7967","authenticated-orcid":false,"given":"Muzammil","family":"Hussain","sequence":"additional","affiliation":[{"name":"Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soung-Yue","family":"Liew","sequence":"additional","affiliation":[{"name":"Faculty of Information and Communication Technology (FICT), Universiti Tunku Abdul Rahman (UTAR), Kampar 31900, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9093-5245","authenticated-orcid":false,"given":"Ivan","family":"Andonovic","sequence":"additional","affiliation":[{"name":"Department of Electronic and Electrical Engineering, Royal College Building, University of Strathclyde, 204 George St., Glasgow G1 1XW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4854-9935","authenticated-orcid":false,"given":"Muhammad Adnan","family":"Khan","sequence":"additional","affiliation":[{"name":"Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam 13557, Korea"},{"name":"Faculty of Computing, Riphah School of Computing and Innovation, Riphah International University, Lahore Campus, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1053\/j.ajkd.2005.05.005","article-title":"Associations between retinal microvascular abnormalities and declining renal function in the elderly population: The Cardiovascular Health Study","volume":"46","author":"Edwards","year":"2005","journal-title":"Am. 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