Carpal tunnel syndrome management: merging traditional therapies with AI for optimal outcomes. | ||
| Deraya International Journal for Medical Sciences and Rehabilitation | ||
| Volume 2, Issue 1, October 2025 PDF (802.38 K) | ||
| Document Type: Review Article | ||
| DOI: 10.21608/dijms.2025.374252.1020 | ||
| Authors | ||
| Wael Gomaa Abdelnaeem* 1; Amany Hussien Helmy2; Mahmoud Yassin Elzanaty3; Asmaa Mahmoud Gamal4; Eslam Mohamed Bakhit5 | ||
| 1Taha Hussein st, Elminya_Egypt | ||
| 2Deraya university, faculty of physical therapy, minya | ||
| 3Vice dean of Education and students affairs of physical therapy college at deraya university | ||
| 4Deraya university, faculty of physical therapy | ||
| 5Deraya University, faculty of physical therapy | ||
| Abstract | ||
| Background: Carpal Tunnel Syndrome (CTS) represents the most common form of peripheral nerve neuropathy of the upper limb. It results in pain, numbness, and limitation of function. Conservative management includes physiotherapy, splinting, and activity modification. As artificial intelligence (AI) becomes increasingly common in healthcare, novel approaches to improve diagnosis, treatment precision, and rehabilitation effectiveness. Methods: This review examines how AI can improve patient outcomes simultaneously with traditional treatments of CTS. We Searched through PubMed, Scopus, and Cochrane Library (2020–2024) yielded 247 articles after applying inclusion/exclusion criteria (e.g., English language, human studies) 15 studies selected using keywords: “carpal tunnel syndrome,” “traditional therapies,” “AI,” “machine learning,” “rehabilitation,” “diagnosis.” from medical databases with focus on AI applications in monitoring of patients (e.g., wearable sensor technology), treatment planning (e.g., robotic-assisted therapy), and diagnosis (e.g. electromyography-based models). Results: 15 studies were reviewed 12 (80%) were randomized controlled trials (RCTs), and 3 (20%) were systematic reviews., published from 2020 to 2024. The studies examined the effect of different modalities and techniques such as shock wave therapy, ultrasound, exercises, and the role of AI in the diagnosis and management of CTS. The primary outcomes assessed in the studies were pain, electrophysiological parameters, and functional improvement. Conclusion: The combination of AI innovations with evidence-based conventional treatments will determine the future of CTS treatment. Healthcare professionals may provide more accurate, flexible, and patient-centered care by integrating AI into clinical practice, which will ultimately reduce the need for invasive techniques . Keywords: Carpal tunnel syndrome, traditional therapies, Artificial intelligence (AI) | ||
| Keywords | ||
| Carpal tunnel syndrome; traditional therapies; Artificial intelligence (AI) | ||
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