{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T23:33:32Z","timestamp":1792193612158,"version":"4.4.0"},"reference-count":52,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,14]],"date-time":"2023-10-14T00:00:00Z","timestamp":1697241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Carpal tunnel syndrome (CTS) is a prevalent medical condition resulting from compression of the median nerve in the hand, often caused by overuse or age-related factors. In this study, a total of 160 patients participated, including 80 individuals with CTS presenting varying levels of severity across different age groups. Numerous studies have explored the use of machine learning (ML) and deep learning (DL) techniques for CTS diagnosis. However, further research is required to fully leverage the potential of artificial intelligence (AI) technology in CTS diagnosis, addressing the challenges and limitations highlighted in the existing literature. In our work, we propose a novel approach for CTS diagnosis, prediction, and monitoring disease progression. The proposed framework consists of three main layers. Firstly, we employ three distinct DL models for CTS diagnosis. Through our experiments, the proposed approach demonstrates superior performance across multiple evaluation metrics, with an accuracy of 0.969%, precision of 0.982%, and recall of 0.963%. The second layer focuses on predicting the cross-sectional area (CSA) at 1, 3, and 6 months using ML models, aiming to forecast disease progression during therapy. The best-performing model achieves an accuracy of 0.9522, an R2 score of 0.667, a mean absolute error (MAE) of 0.0132, and a median squared error (MdSE) of 0.0639. The highest predictive performance is observed after 6 months. The third layer concentrates on assessing significant changes in the patients\u2019 health status through statistical tests, including significance tests, the Kruskal-Wallis test, and a two-way ANOVA test. These tests aim to determine the effect of injections on CTS treatment. The results reveal a highly significant reduction in symptoms, as evidenced by scores from the Symptom Severity Scale and Functional Status Scale, as well as a decrease in CSA after 1, 3, and 6 months following the injection. SHAP is then utilized to provide an understandable explanation of the final prediction. Overall, our study presents a comprehensive approach for CTS diagnosis, prediction, and monitoring, showcasing promising results in terms of accuracy, precision, and recall for CTS diagnosis, as well as effective prediction of disease progression and evaluation of treatment effectiveness through statistical analysis.<\/jats:p>","DOI":"10.3390\/diagnostics13203211","type":"journal-article","created":{"date-parts":[[2023,10,14]],"date-time":"2023-10-14T14:38:42Z","timestamp":1697294322000},"page":"3211","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Deep Learning-Based Approaches for Enhanced Diagnosis and Comprehensive Understanding of Carpal Tunnel Syndrome"],"prefix":"10.3390","volume":"13","author":[{"given":"Marwa","family":"Elseddik","sequence":"first","affiliation":[{"name":"Department of the Robotics and Internet Machines, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33516, Egypt"},{"name":"Department of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khaled","family":"Alnowaiser","sequence":"additional","affiliation":[{"name":"College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al Kharj 11942, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6917-7873","authenticated-orcid":false,"given":"Reham R.","family":"Mostafa","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt"},{"name":"Research Institute of Sciences and Engineering (RISE), University of Sharjah, Sharjah 27272, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6618-0479","authenticated-orcid":false,"given":"Ahmed","family":"Elashry","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Kafrelsheikh University, Kafrelsheikh 33516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8177-9439","authenticated-orcid":false,"given":"Nora","family":"El-Rashidy","sequence":"additional","affiliation":[{"name":"Department of Machine Learning and Information Retrieval, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh 33516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shimaa","family":"Elgamal","sequence":"additional","affiliation":[{"name":"Department of Neuropsychiatry, Faculty of Medicine, Kafrelsheikh University, Kafrelsheikh 33516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed","family":"Aboelfetouh","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt"},{"name":"Delta Higher Institute for Management and Accounting Information Systems, Mansoura 35511, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hazem","family":"El-Bakry","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Mansoura University, Mansoura 35516, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.2106\/00004623-199311000-00002","article-title":"A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome","volume":"75","author":"Levine","year":"1993","journal-title":"J. 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