Prediction of neuropathy, neuropathic pain and kinesiophobia in patients with type 2 diabetes and design of computerized clinical decision support systems by using artificial intelligence

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dc.authoridSahin, Ibrahim/0000-0002-6231-0034
dc.authoridHanbay, Davut/0000-0003-2271-7865
dc.authoridOzdemir, Filiz/0000-0001-9421-0233
dc.authoridKILCIK, Melek Havva/0000-0001-9744-0472
dc.authorwosidSahin, Ibrahim/ABI-6050-2020
dc.authorwosidARI, ALİ/ABH-1602-2020
dc.authorwosidHanbay, Davut/AAG-8511-2019
dc.authorwosidOzdemir, Filiz/GXW-2763-2022
dc.authorwosidŞahin, İbrahim/HHY-8303-2022
dc.contributor.authorOzdemir, Filiz
dc.contributor.authorAri, Ali
dc.contributor.authorKilcik, Melek Havva
dc.contributor.authorHanbay, Davut
dc.contributor.authorSahin, Ibrahim
dc.date.accessioned2024-08-04T20:48:44Z
dc.date.available2024-08-04T20:48:44Z
dc.date.issued2020
dc.departmentİnönü Üniversitesien_US
dc.description.abstractExercise is a key component for prevention and treatment of type 2 diabetes. However, diabetes complications affect exercise habits. Computerized clinical decision support systems (CCDSSs) may help specialists improve their decision-making abilities in the management of diseases. We hypothesized that patients' diabetic neuropathy, neuropathic pain, and kinesiophobia will quickly be identified in the early stages by using the designed CCDSSs. It is thought that such systems will help in planning exercise programs for patients with diabetes and in maintaining the appropriate programs. Based on our hypothesis, we conclude that CCDSSs will also be effective in managing complications and movement dysfunctions occurring in the musculoskeletal system.en_US
dc.identifier.doi10.1016/j.mehy.2020.110070
dc.identifier.issn0306-9877
dc.identifier.issn1532-2777
dc.identifier.pmid32683220en_US
dc.identifier.scopus2-s2.0-85087960782en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1016/j.mehy.2020.110070
dc.identifier.urihttps://hdl.handle.net/11616/99416
dc.identifier.volume143en_US
dc.identifier.wosWOS:000577511800095en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofMedical Hypothesesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNeuropathyen_US
dc.subjectNeuropathic painen_US
dc.subjectKinesiophobiaen_US
dc.subjectType 2 diabetesen_US
dc.subjectArtificial neural networksen_US
dc.titlePrediction of neuropathy, neuropathic pain and kinesiophobia in patients with type 2 diabetes and design of computerized clinical decision support systems by using artificial intelligenceen_US
dc.typeArticleen_US

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