| "Carpal Tunnel Syndrome Management: Merging Traditional Therapies with AI for Optimal Outcomes: A Narrative Review" |
| Paper ID : 1057-ISCSR3 (R1) |
| Authors |
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Eslam Mohamed Bakhit *1, Asmaa Mahmoud Gamal2, Mahmoud Yassin Elzanaty3, Wael Gomaa Abdelnaeem4, Amany Hussien Helmy5 1Student at Faculty of Physical therapy, Deraya university 2Student at Faculty of Physical therapy, Deraya University 3Vice Dean for Education and Student affairs , Faculty of Physical Therapy, Deraya University 4Instructor at Faculty of Physical therapy, Deraya university 5Student at Faculty of physical therapy, Deraya University |
| Abstract |
| Background: Carpal Tunnel Syndrome (CTS) represents the most common form of peripheral nerve neuropathy of the upper limb. Conservative management includes physiotherapy, splinting, and activity modification, while corticosteroid injections and surgery are invasive or minimally invasive options. As artificial intelligence (AI) becomes increasingly common in healthcare, novel approaches to improve diagnosis, treatment precision, and rehabilitation effectiveness. Methods: This narrative review examines how AI can improve patient outcomes simultaneously summarizing the most recently published studies on traditional treatments of CTS. We Searched through PubMed, Scopus, IEEE Xplore, and Cochrane Library (2020–2024) yielded 247 articles after applying inclusion/exclusion criteria (e.g., English language, human studies) 15 studies were selected by using keywords: “carpal tunnel syndrome,” “traditional therapies,” “AI,” “machine learning,” “rehabilitation,” “diagnosis.” through reviewing 15 studies from medical databases with focus on AI applications in monitoring of patients (e.g., wearable sensor technology), treatment planning (e.g., robotic-assisted therapy, AI-guided rehabilitation), and diagnosis (e.g., machine learning algorithms, electromyography-based models). Results: A total of 15 studies were reviewed around 12 (80%) were randomized controlled trials (RCTs), and 3 (20%) were systematic reviews., published from 2020 to 2024. The majority of these studies were randomized controlled trials, followed by systematic reviews. The studies examined the effect of different modalities and techniques such as shock wave therapy, ultrasound, low-level laser therapy, manual therapy, 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: Merging AI with traditional CTS treatments has positive impact to revolutionize management of carpal tunnel syndrome. 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) |
| Status: Abstract Accepted |