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A Literature Review on Artificial Intelligence Methods Related to Low Back Pain
1University of Health Sciences, Health Care Management, Istanbul, Turkey
2University of Health Sciences, Health Care Management, Istanbul, Turkey
3International School of Medicine, University of Health Sciences, Department of Anesthesiology and Reanimation
2026-03-05
2026-03-20
2026-03-30
Abstract
Low back pain (LBP) is a worldwide health problem caused by various diseases. It is difficult to establish standards in medical applications because of the differences in the causes of its occurrence and the individual effects in treatment. The LBP diagnosis and treatment processes generate different numerical and visual data. Today, artificial intelligence (AI) techniques have begun to be developed, aiming to improve the understanding of LBP's causes, treatment processes, and effectiveness using patient data. In our study, we aimed to systematically search the literature on the diagnosis and treatment processes of LBP using AI techniques. We conducted a systematic review of studies on LBP utilizing AI methods between 01.01.2000 and 01.05.2023, using the PubMed database. While searching the database, combinations of the terms "Artificial Intelligence," "Machine Learning," "Deep Learning," and "Low Back Pain" were employed. A total of 369 articles were identified. According to the study inclusion criteria, 354 articles were excluded, and 15 studies were reviewed. Magnetic resonance images, biochemical parameters, kinematic variables, EMG signals, PET imaging, and other variables were used AI methods to diagnose LBP. The studies employing AI methods generally focused on classification and regression problems. The AI techniques developed for the diagnosis and treatment processes of LBP are promising. It is anticipated that multidisciplinary studies using artificial intelligence.