Use of Machine Learning and Artificial Intelligence in Diabetes
| dc.contributor.author | Sezen, Bülent | |
| dc.contributor.author | Sertbakan, Kubra | |
| dc.date.accessioned | 2025-10-29T12:10:02Z | |
| dc.date.issued | 2024 | |
| dc.department | Gebze Teknik Üniversitesi | |
| dc.description.abstract | Diabetes has become a common and endemic health problem worldwide. In the face of such a health problem, healthcare services seek help from technological developments to combat this disease. As in every field, Artificial Intelligence applications in healthcare are being discussed more and more every day. Among the most promising technological frontiers in healthcare is Machine Learning, a subset of Artificial Intelligence that can analyze vast amounts of data, identify patterns, and predict outcomes. Machine Learning has the potential to revolutionize diabetes management by providing valuable insights into patient health, informing treatment decisions, and predicting a person's risk of developing the disease in the future. Within the scope of this section, Artificial Intelligence and Machine Learning methods and their results used in research on early diagnosis, diagnosis and prediction of diabetes have been examined within the scope of literature review. © 2025 Elsevier B.V., All rights reserved. | |
| dc.identifier.doi | 10.4018/979-8-3693-9641-4.ch006 | |
| dc.identifier.endpage | 204 | |
| dc.identifier.isbn | 9798369396438 | |
| dc.identifier.isbn | 9798369396414 | |
| dc.identifier.scopus | 2-s2.0-105008855697 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 177 | |
| dc.identifier.uri | https://doi.org/10.4018/979-8-3693-9641-4.ch006 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14854/14923 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | IGI Global | |
| dc.relation.publicationcategory | Kitap Bölümü - Uluslararası | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_Scopus_20251020 | |
| dc.subject | Diagnosis | |
| dc.subject | Health risks | |
| dc.subject | Learning systems | |
| dc.subject | Machine learning | |
| dc.subject | Patient treatment | |
| dc.subject | Technological forecasting | |
| dc.subject | Artificial intelligence learning | |
| dc.subject | Diabetes management | |
| dc.subject | Early diagnosis | |
| dc.subject | Early prediction | |
| dc.subject | Healthcare services | |
| dc.subject | Literature reviews | |
| dc.subject | Machine learning methods | |
| dc.subject | Machine-learning | |
| dc.subject | Patient health | |
| dc.subject | Technological development | |
| dc.subject | Medical problems | |
| dc.title | Use of Machine Learning and Artificial Intelligence in Diabetes | |
| dc.type | Book Chapter |









