{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T02:49:57Z","timestamp":1792810197081,"version":"4.5.0"},"reference-count":15,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T00:00:00Z","timestamp":1717113600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["THC"],"published-print":{"date-parts":[[2024,5,31]]},"abstract":"<jats:p>BACKGROUND: This study utilizes machine learning to analyze the recurrence risk of diabetic foot ulcers (DFUs) in elderly diabetic patients, aiming to enhance prevention and intervention efforts. OBJECTIVE: The goal is to construct accurate predictive models for assessing the recurrence risk of DFUs based on high-risk factors, such as age, blood sugar control, alcohol consumption, and smoking, in elderly diabetic patients. METHODS: Data from 138 elderly diabetic patients were collected, and after data cleaning, outlier screening, and feature integration, machine learning models were constructed. Support Vector Machine (SVM) was employed, achieving an accuracy rate of 93%. RESULTS: Experimental results demonstrate the effectiveness of SVM in predicting the recurrence risk of DFUs in elderly diabetic patients, providing clinicians with a more accurate tool for assessment. CONCLUSIONS: The study highlights the significance of machine learning in managing foot ulcers in elderly diabetic patients, particularly in predicting recurrence risk. This approach facilitates timely intervention, reducing the likelihood of patient recurrence, and introduces computer-assisted medical strategies in elderly diabetes management.<\/jats:p>","DOI":"10.3233\/thc-248023","type":"journal-article","created":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T11:01:47Z","timestamp":1715684507000},"page":"265-276","source":"Crossref","is-referenced-by-count":15,"title":["Personalized prediction of diabetic foot ulcer recurrence in elderly individuals using machine learning paradigms"],"prefix":"10.1177","volume":"32","author":[{"given":"Shichai","family":"Hong","sequence":"first","affiliation":[{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"},{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihui","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"},{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinsheng","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hefu","family":"Xie","sequence":"additional","affiliation":[{"name":"Xiamen University School of Information Science and Technology, Xiamen University Xiang\u2019an Campus, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weifeng","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Vascular Surgery, Zhongshan Hospital (Xiamen), Fudan University, Huli District, Xiamen, Fujian, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"issue":"24","key":"10.3233\/THC-248023_ref1","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1056\/NEJMra1615439","article-title":"Diabetic foot ulcers and their recurrence","volume":"376","author":"Armstrong","year":"2017","journal-title":"New England Journal of Medicine."},{"issue":"1","key":"10.3233\/THC-248023_ref2","first-page":"65","article-title":"Foot ulcers in the diabetic patient, prevention and treatment","volume":"3","author":"Wu","year":"2007","journal-title":"Vascular Health and Risk Management."},{"issue":"5","key":"10.3233\/THC-248023_ref3","doi-asserted-by":"crossref","first-page":"1435","DOI":"10.2337\/diacare.26.5.1435","article-title":"Diabetic foot syndrome: Evaluating the prevalence and incidence of foot pathology in Mexican Americans and non-Hispanic whites from a diabetes disease management cohort","volume":"26","author":"Lavery","year":"2003","journal-title":"Diabetes Care."},{"key":"10.3233\/THC-248023_ref4","unstructured":"Jeffcoate WJ, Price PE, Phillips CJ, Game FL, Mudge E. 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Health Technology Assessment. 2004; 8(29): iii-iv, 1-114."},{"issue":"5","key":"10.3233\/THC-248023_ref5","first-page":"369","article-title":"The management of diabetic foot ulcers through optimal off-loading: Building consensus guidelines and practical recommendations to improve outcomes","volume":"100","author":"Snyder","year":"2010","journal-title":"Journal of the American Podiatric Medical Association."},{"issue":"6","key":"10.3233\/THC-248023_ref6","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1111\/iwj.13200","article-title":"Risk factors for the recurrence of diabetic foot ulcers among diabetic patients: A meta-analysis","volume":"16","author":"Huang","year":"2019","journal-title":"International Wound Journal."},{"issue":"1","key":"10.3233\/THC-248023_ref8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13098-022-00969-9","article-title":"Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: A comprehensive review","volume":"14","author":"Afsaneh","year":"2022","journal-title":"Diabetology & Metabolic Syndrome."},{"issue":"8","key":"10.3233\/THC-248023_ref9","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1007\/s11517-022-02617-w","article-title":"Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity","volume":"60","author":"Nanda","year":"2022","journal-title":"Medical & Biological Engineering & Computing."},{"key":"10.3233\/THC-248023_ref11","doi-asserted-by":"crossref","first-page":"974063","DOI":"10.3389\/fendo.2022.974063","article-title":"Impact of acute hyperglycemic crisis episode on survival in individuals with diabetic foot ulcer using a machine learning approach","volume":"13","author":"Deng","year":"2022","journal-title":"Frontiers in Endocrinology."},{"issue":"2","key":"10.3233\/THC-248023_ref12","first-page":"691","article-title":"Implementation of KNN algorithm in classifying diabetic ulcers in patients with diabetes mellitus","volume":"7","author":"Siregar","year":"2023","journal-title":"Jurnal Mantik."},{"key":"10.3233\/THC-248023_ref13","doi-asserted-by":"crossref","first-page":"198977","DOI":"10.1109\/ACCESS.2020.3035327","article-title":"Machine learning in the prevention, diagnosis and management of diabetic foot ulcers: A systematic review","volume":"8","author":"Tulloch","year":"2020","journal-title":"IEEE Access."},{"key":"10.3233\/THC-248023_ref15","doi-asserted-by":"crossref","unstructured":"Wouter B, Abu-Hanna A, Bus SA. Development of a multivariable prediction model for plantar foot ulcer recurrence in high-risk people with diabetes. BMJ Open Diabetes Research & Care. 2020; 8(1).","DOI":"10.1136\/bmjdrc-2020-001207"},{"key":"10.3233\/THC-248023_ref16","doi-asserted-by":"crossref","unstructured":"Abaker AA, Saeed FA. A comparative analysis of machine learning algorithms to build a predictive model for detecting diabetes complications. Informatica. 2021; 45(1).","DOI":"10.31449\/inf.v45i1.3111"},{"key":"10.3233\/THC-248023_ref17","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.jss.2019.09.025","article-title":"Incidence and risk factors associated with ulcer recurrence among patients with diabetic foot ulcers treated in a multidisciplinary setting","volume":"246","author":"Hicks","year":"2020","journal-title":"Journal of Surgical Research."},{"key":"10.3233\/THC-248023_ref18","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.future.2022.10.019","article-title":"Identifying patterns in multiple biomarkers to diagnose diabetic foot using an explainable genetic programming-based approach","volume":"140","author":"D\u2019Angelo","year":"2023","journal-title":"Future Generation Computer Systems."}],"container-title":["Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/THC-248023","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:20:58Z","timestamp":1777612858000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/THC-248023"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,31]]},"references-count":15,"URL":"https:\/\/doi.org\/10.3233\/thc-248023","relation":{},"ISSN":["0928-7329","1878-7401"],"issn-type":[{"value":"0928-7329","type":"print"},{"value":"1878-7401","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,31]]}}}