Table 3.

Potential Applications of AI in Spinal Disease Care.

Area of Spinal Disease Care	Description
Diagnosis and Detection	AI can assist in the automated analysis of medical imaging data, such as MRI or CT scans, for the detection and segmentation of spinal conditions, such as spinal stenosis. AI algorithms can aid in accurate and efficient diagnosis, providing valuable insights for healthcare professionals.
Treatment Planning	AI can support healthcare professionals in personalized treatment planning for spinal diseases. By analyzing patient data, including medical images, clinical records, and outcomes, AI algorithms can help determine the most appropriate treatment options and assist in surgical technique selection.
Surgical Guidance	AI can provide real-time guidance during spinal surgeries. By integrating pre-operative imaging data and intraoperative feedback, AI systems can help surgeons navigate complex spinal anatomies and make informed decisions, leading to improved surgical outcomes.
Predictive Modeling	AI can develop predictive models to assess disease progression and treatment outcomes for spinal diseases. These models can aid in prognosticating patient outcomes, optimizing treatment strategies, and facilitating shared decision making between healthcare providers and patients.
Rehabilitation Support	AI can assist in designing personalized rehabilitation programs for patients with spinal diseases. By analyzing patient data, including movement patterns and sensor data, AI algorithms can provide customized recommendations and monitoring during the rehabilitation process.
Remote Monitoring	AI-enabled remote monitoring systems can help track and monitor patients with spinal diseases outside of healthcare facilities. These systems can provide continuous monitoring, detect changes in symptoms or movement patterns, and alert healthcare providers for timely intervention.