| Effect of Artificial Intelligence-based Interventions on Pain and Functional Outcomes in Patients with Low Back Pain: A Narrative Review" |
| Paper ID : 1018-ISCSR3 (R1) |
| Authors |
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Doaa Abdel Hady *1, abdelazim hussein2, abdelrahman mohamed2 1Head of physical therapy for the women's health department 2Student at Faculty of Physical Therapy, Deraya University, Minia, Egypt. |
| Abstract |
| The review is dedicated to understanding the potential of artificial intelligence (AI) applications and algorithms in physical therapy and rehabilitation, especially focusing on patients experiencing low back pain (LBP). The review highlighted the joint positive and negative impacts of machine learning techniques and AI on improving health outcomes. Methods: The narrative review discussed the application of AI with specified LBP patients; we also included only clinical trials, English-language studies, and studies that were published between 2019 and 2025. Any study that didn’t meet our inclusion criteria was excluded. WOS, Scopus, PubMed, and IEEE Xplore were our sourced databases. Two reviewers conducted title/abstract and full-text screening. Data were gathered on input variables, model type, machine learning techniques, and predicted outcomes. Results: Articles published between 2019 and 2025, including 1365 participants ranging from postpartum women to elderly patients, focusing particularly on LBP and AI, including 12 papers illustrating a range of AI applications, including the "self-back app," a mobile application designed for prediction, self-mentoring, and even self-guided management of patients suffering from LBP, expounding remarkable positive outcomes. Furthermore, convolutional neural networks (CNNs), a computational method, were hired to analyze medical images and identify specific weak back muscles, aiding physiotherapists in designing targeted interventions. AI was also utilized to show the suitability of acute LBP patients for specific treatments based on gathered data. However, some studies showed that AI interventions are not universally efficient. Not as expected, Conclusion: AI is remodeling physical therapy, especially in managing LBP. This shift is expressed in studies on real-time exercise feedback via mobile applications, analysis of trunk movements, and machine learning-based classification in individuals with CLBP. Furthermore, medical expert systems leveraging Bayesian networks offer innovative and personalized management strategies, remodeling the future of physical therapy. |
| Keywords |
| Artificial intelligence – Low back pain – trials – Applications -machine learning – Physical therapy |
| Status: Abstract Accepted |