@article{10.37349/emd.2026.1007126,
abstract = {Precision Spine Care integrates individualized diagnostics and interventions tailored to the unique anatomical and clinical characteristics of each patient. Recent advances in artificial intelligence (AI) and machine learning are addressing these challenges by enabling automated image interpretation, tissue segmentation, quantitative analysis of muscular and fascial features, and longitudinal tracking of structural and functional changes. These AI-driven capabilities support objective assessment, early detection of pathology, personalized rehabilitation planning, and continuous monitoring of treatment response. This approach becomes increasingly complex when incorporating advanced interventional techniques such as ultrasound-guided pain injections and AI tools. AI facilitates automated image interpretation, tissue characterization, and structure recognition, improving efficiency and diagnostic consistency. Augmented reality (AR) and mixed reality (MR) technologies enhance spatial orientation, procedural guidance, and anatomy education, while tele-ultrasound expands access to expert consultation, imaging support, and training in underserved regions. Although ultrasound remains operator dependent and AI outputs require ongoing physician oversight, the integration of ultrasound with AI, AR/MR, and telemedicine represents a significant advancement in spine care. These technologies complement traditional anatomical and clinical approaches, improving diagnostic accuracy, procedural precision, and personalized rehabilitation strategies. As healthcare systems face increasing demand and workforce constraints, technology-assisted ultrasound is positioned to play a pivotal role in advancing spine assessment, education, and comprehensive spine-focused musculoskeletal management. Ultimately, AI, ultrasound, and telemedicine serve to augment, not replace clinicians, enabling precision spine care that is safe, effective, and patient-centered.},
author = {Gharaei, Helen and Gupta, Pranshul and Bagherian, Ziba and Mahalwar, Sonal},
doi = {10.37349/emd.2026.1007126},
journal = {Exploration of Musculoskeletal Diseases},
elocation-id = {1007126},
title = {AI-driven spine-focused musculoskeletal management},
url = {https://www.explorationpub.com/Journals/emd/Article/1007126},
volume = {4},
year = {2026}
}