{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T00:55:36Z","timestamp":1769734536001,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T00:00:00Z","timestamp":1724025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Management Centre, Multimedia University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Bibliometric analysis is a rigorous method to analyze significant quantities of bibliometric data to assess their impact on a particular field. This study used bibliometric analysis to investigate the academic research on diabetes detection and classification from 2000 to 2023. The PRISMA 2020 framework was followed to identify, filter, and select relevant papers. This study used the Web of Science database to determine relevant publications concerning diabetes detection and classification using the keywords \u201cdiabetes detection\u201d, \u201cdiabetes classification\u201d, and \u201cdiabetes detection and classification\u201d. A total of 863 publications were selected for analysis. The research applied two bibliometric techniques: performance analysis and science mapping. Various bibliometric parameters, including publication analysis, trend analysis, citation analysis, and networking analysis, were used to assess the performance of these articles. The analysis findings showed that India, China, and the United States are the top three countries with the highest number of publications and citations on diabetes detection and classification. The most frequently used keywords are machine learning, diabetic retinopathy, and deep learning. Additionally, the study identified \u201cclassification\u201d, \u201cdiagnosis\u201d, and \u201cvalidation\u201d as the prevailing topics for diabetes identification. This research contributes valuable insights into the academic landscape of diabetes detection and classification.<\/jats:p>","DOI":"10.3390\/s24165346","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T06:41:31Z","timestamp":1724049691000},"page":"5346","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Analyzing Diabetes Detection and Classification: A Bibliometric Review (2000\u20132023)"],"prefix":"10.3390","volume":"24","author":[{"given":"Jannatul","family":"Ferdaus","sequence":"first","affiliation":[{"name":"Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Esmay Azam","family":"Rochy","sequence":"additional","affiliation":[{"name":"Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8489-3827","authenticated-orcid":false,"given":"Uzzal","family":"Biswas","sequence":"additional","affiliation":[{"name":"Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1178-9356","authenticated-orcid":false,"given":"Jun Jiat","family":"Tiang","sequence":"additional","affiliation":[{"name":"Centre for Wireless Technology (CWT), Faculty of Engineering, Multimedia University, Cyberjaya 63100, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdullah-Al","family":"Nahid","sequence":"additional","affiliation":[{"name":"Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alamro, H., Bajic, V., Macvanin, M.T., Isenovic, E.R., Gojobori, T., Essack, M., and Gao, X. 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