{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T02:22:41Z","timestamp":1769307761804,"version":"3.49.0"},"reference-count":54,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T00:00:00Z","timestamp":1670803200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Support Fund (RSF) of Symbiosis International (Deemed University)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>Diabetic retinopathy (DR) is a medical condition caused by diabetes. The development of retinopathy significantly depends on how long a person has had diabetes. Initially, there may be no symptoms or just a slight vision problem due to impairment of the retinal blood vessels. Later, it may lead to blindness. Recognizing the early clinical signs of DR is very important for intervening in and effectively treating DR. Thus, regular eye check-ups are necessary to direct the person to a doctor for a comprehensive ocular examination and treatment as soon as possible to avoid permanent vision loss. Nevertheless, due to limited resources, it is not feasible for screening. As a result, emerging technologies, such as artificial intelligence, for the automatic detection and classification of DR are alternative screening methodologies and thereby make the system cost-effective. People have been working on artificial-intelligence-based technologies to detect and analyze DR in recent years. This study aimed to investigate different machine learning styles that are chosen for diagnosing retinopathy. Thus, a bibliometric analysis was systematically done to discover different machine learning styles for detecting diabetic retinopathy. The data were exported from popular databases, namely, Web of Science (WoS) and Scopus. These data were analyzed using Biblioshiny and VOSviewer in terms of publications, top countries, sources, subject area, top authors, trend topics, co-occurrences, thematic evolution, factorial map, citation analysis, etc., which form the base for researchers to identify the research gaps in diabetic retinopathy detection and classification.<\/jats:p>","DOI":"10.3390\/bdcc6040154","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T05:42:00Z","timestamp":1670823720000},"page":"154","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Machine Learning Styles for Diabetic Retinopathy Detection: A Review and Bibliometric Analysis"],"prefix":"10.3390","volume":"6","author":[{"given":"Shyamala","family":"Subramanian","sequence":"first","affiliation":[{"name":"Symbiosis Institute of Technology, Pune (SIT), Symbiosis International (Deemed) University (SIU), Pune 412115, India"},{"name":"Department of Electronics and Telecommunication, SIES Graduate School of Technology, Navi Mumbai 400706, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sashikala","family":"Mishra","sequence":"additional","affiliation":[{"name":"Symbiosis Institute of Technology, Pune (SIT), Symbiosis International (Deemed) University (SIU), Pune 412115, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4903-1540","authenticated-orcid":false,"given":"Shruti","family":"Patil","sequence":"additional","affiliation":[{"name":"Symbiosis Centre for Applied Artificial Intelligence (SCAAI), Symbiosis Institute of Technology, Symbiosis International (Deemed) University (SIU), Pune 412115, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5677-7423","authenticated-orcid":false,"given":"Kailash","family":"Shaw","sequence":"additional","affiliation":[{"name":"Symbiosis Institute of Technology, Pune (SIT), Symbiosis International (Deemed) University (SIU), Pune 412115, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ebrahim","family":"Aghajari","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz 61349-37333, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1580","DOI":"10.1016\/j.ophtha.2021.04.027","article-title":"Global prevalence of diabetic retinopathy and projection of burden through 2045: Systematic review and meta-analysis","volume":"128","author":"Teo","year":"2021","journal-title":"Ophthalmology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3087","DOI":"10.4103\/ijo.IJO_1310_21","article-title":"Prevalence of diabetic retinopahty in India: Results from the National Survey 2015\u201319","volume":"69","author":"Vashist","year":"2021","journal-title":"Indian J. 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