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. (October 2020)

• Record Type: Journal Article
• Authors: Ozdemir, Filiz; Ari, Ali; Kilcik, Melek Havva; Hanbay, Davut; Sahin, Ibrahim
• Is Part Of: Medical hypotheses. Volume 143(2020)
• Publication Date: 2020-10
• Subjects: Neuropathy -- Neuropathic pain -- Kinesiophobia -- Type 2 diabetes -- Artificial neural networks; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Medicine; Periodicals; 610
• DOI: 10.1016/j.mehy.2020.110070
• Languages: English
• ISSNs: 0306-9877

Abstract

Abstract: Exercise 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.