{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T17:23:19Z","timestamp":1793726599778,"version":"4.6.1"},"reference-count":29,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,2,17]],"date-time":"2025-02-17T00:00:00Z","timestamp":1739750400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Directorate of Innovation and Science Technology (AI Center) Universitas Brawijaya","award":["00067.09\/UN10.A0507\/B\/KS\/2024"],"award-info":[{"award-number":["00067.09\/UN10.A0507\/B\/KS\/2024"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Diabetes Sci Technol"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction:<\/jats:title>\n                    <jats:p>Early detection of diabetic foot complications is essential for effective management and prevention of complications. Artificial intelligence (AI) technology based on digital image analysis offers a promising noninvasive method for diabetic foot screening. This systematic review aims to identify a study on the development of an AI model for diabetic foot screening using digital image analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methodology:<\/jats:title>\n                    <jats:p>The review scrutinized articles published between 2018 and 2023, sourced from PubMed, ProQuest, and ScienceDirect. The keyword-based search resulted in 2214 relevant articles and nine articles that met the inclusion criteria. The article quality assessment was done through Quality Assessment of Diagnostic Accuracy Studies (QUADAS). Data were extracted and analyzed using NVivo.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Thermal imagery or foot thermogram was the main data source, with plantar temperature distribution patterns as an important indicator. Deep learning methods, specifically artificial neural networks (ANNs) and convolutional neural networks (CNNs), are the most commonly used methods. The highest performance is demonstrated by the ANN model with MATLAB\u2019s Image Processing Toolbox that is able to classify each type of macula with 97.5% accuracy. The findings show the great potential of AI in improving the accuracy and efficiency of diabetic foot screening.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>This research provides important insights into the development of AI in digital image\u2013based diabetic foot screening. Future studies need to focus on evaluating clinical applicability, including ethical aspects and patient data security, as well as developing more comprehensive data sets.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/19322968251317521","type":"journal-article","created":{"date-parts":[[2025,2,17]],"date-time":"2025-02-17T08:19:26Z","timestamp":1739780366000},"page":"1381-1388","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Artificial Intelligence for Diabetic Foot Screening Based on Digital Image Analysis: A Systematic Review"],"prefix":"10.1177","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0213-5689","authenticated-orcid":false,"given":"Ni Kadek Indah Sunar","family":"Anggreni","sequence":"first","affiliation":[{"name":"Nursing Department, Faculty of Health Sciences, Brawijaya University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9869-4519","authenticated-orcid":false,"given":"Heri","family":"Kristianto","sequence":"additional","affiliation":[{"name":"Nursing Department, Faculty of Health Sciences, Brawijaya University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9018-0233","authenticated-orcid":false,"given":"Dian","family":"Handayani","sequence":"additional","affiliation":[{"name":"Nutrition Department, Faculty of Health Sciences, Brawijaya University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9932-2015","authenticated-orcid":false,"given":"Yuyun","family":"Yueniwati","sequence":"additional","affiliation":[{"name":"Radiology Department, Faculty of Medicine, Brawijaya University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2907-6223","authenticated-orcid":false,"given":"Paulus Lucky Tirma","family":"Irawan","sequence":"additional","affiliation":[{"name":"Informatics Engineering Department, Faculty of Technology and Design, Ma Chung University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4814-5842","authenticated-orcid":false,"given":"Rulli","family":"Rosandi","sequence":"additional","affiliation":[{"name":"Internal Medicine Department, Dr Saiful Anwar General Hospital, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7016-0136","authenticated-orcid":false,"given":"Rinik Eko","family":"Kapti","sequence":"additional","affiliation":[{"name":"Nursing Department, Faculty of Health Sciences, Brawijaya University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8292-455X","authenticated-orcid":false,"given":"Avief Destian","family":"Purnama","sequence":"additional","affiliation":[{"name":"Nursing Department, Faculty of Health Sciences, Brawijaya University, Malang, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,2,17]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-821070-3.00007-6"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1937\/1\/012049"},{"issue":"1","key":"e_1_3_3_4_2","first-page":"35","article-title":"Diabetic foot surveillance using mobile phones and automated software messaging, a randomized observational trial","volume":"40","author":"Anthony CA","year":"2020","unstructured":"Anthony CA, Femino JE, Miller AC, et al. 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