Publication: Artıfıcıal ıntellıgence–based autonomous socket proposal program: A prelımınary study for clınıcal decısıon support system
| dc.contributor.author | Çinar, Murat Ali | |
| dc.contributor.author | Haznedar, Bülent | |
| dc.contributor.author | Bayramlar, Kezban | |
| dc.contributor.author | Çınar, Murat Ali | |
| dc.date.accessioned | 2024-09-18T06:47:08Z | |
| dc.date.available | 2024-09-18T06:47:08Z | |
| dc.date.issued | 27 August 2024 | en_US |
| dc.department | HKÜ, Sağlık Bilimleri Fakültesi, Fizyoterapi ve Rehabilitasyon Bölümü | en_US |
| dc.description.abstract | Purpose: The aim of this study is to develop artificial intelligence-based interfaces that can be used by professionals (clinicians and/or academics) working with disabled individuals who need prosthetics and to create a sample data set for professionals working in this field. Methods: 101 patients who had undergone amputation were enrolled. The residual limbs of all patients were scanned using a three-dimensional (3D) scanner and saved on the computer. The prosthetic sockets, fabricated using traditional methods, were also scanned with the same scanner and saved as a 3D model. Residual limb–prosthetic socket matches were obtained using data points and a deep neural network (DNN)-based decision support system was developed. Results: Simulation studies conducted with the point cloud data sets of 101 patients yielded a training success rate of 86%. The DNN model exhibited a generalization success rate of 78%. Conclusion: The artificial intelligence–based software interface has potential and could assist professionals by suggesting a suitable 3D socket model for patients in need of a prosthesis. Further studies will benefit from additional sample data to enhance the accuracy of the model. © 2024 Turkish Physiotherapy Association. All rights reserved. | en_US |
| dc.identifier.citation | Cinar M.A., Haznedar B. & Bayramlar K. (27 August 2024). Artıfıcıal ıntellıgence–based autonomous socket proposal program: A prelımınary study for clınıcal decısıon support system. Turkish Journal of Physiotherapy and Rehabilitation. ( 35, 2, 206-213.). https://doi.org/10.21653/tjpr.1421321. | en_US |
| dc.identifier.doi | 10.21653/tjpr.1421321 | |
| dc.identifier.endpage | 213 | en_US |
| dc.identifier.issn | 26514451 | |
| dc.identifier.issue | 2 | en_US |
| dc.identifier.orcid | 0000-0003-2122-3759 | en_US |
| dc.identifier.scopus | 2-s2.0-85202678059 | |
| dc.identifier.scopusquality | Q4 | |
| dc.identifier.startpage | 206 | en_US |
| dc.identifier.uri | https://doi.org/10.21653/tjpr.1421321 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11782/4439 | |
| dc.identifier.volume | 35 | en_US |
| dc.identifier.wos | WOS:001320678400009 | |
| dc.identifier.wosquality | Q4 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.indekslendigikaynak | TR-Dizin | |
| dc.language.iso | en | |
| dc.publisher | Turkish Physiotherapy Association | en_US |
| dc.relation.ispartof | Turkish Journal of Physiotherapy and Rehabilitation | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/restrictedAccess | en_US |
| dc.snmz | HKUDK | |
| dc.subject | Amputation | en_US |
| dc.subject | Artificial Intelligence | en_US |
| dc.subject | Decision Support System | en_US |
| dc.title | Artıfıcıal ıntellıgence–based autonomous socket proposal program: A prelımınary study for clınıcal decısıon support system | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 6eaf55d2-f744-4863-a096-d2ba24d6b441 | |
| relation.isAuthorOfPublication.latestForDiscovery | 6eaf55d2-f744-4863-a096-d2ba24d6b441 |
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