Abstract Machine learning algorithms have the potential to significantly improve patient safety in spine surgeries by providing healthcare professionals with valuable insights and predictive analytics. These algorithms can analyze preoperative data, such as patient demographics, medical history, and imaging studies, to identify potential risk factors and predict postoperative complications. By leveraging machine learning, surgeons can make more informed decisions, personalize treatment plans, and optimize surgical techniques to minimize risks and enhance patient outcomes. Moreover, by harnessing the power of machine learning, healthcare providers can make data-driven decisions, personalize treatment plans, and optimize surgical interventions, ultimately enhancing the quality of care in spine surgery. The findings highlight the potential of integrating artificial intelligence in healthcare settings to mitigate risks and enhance patient safety in surgical practices. The integration of machine learning holds immense potential for enhancing patient safety in spine surgeries. By leveraging advanced algorithms and predictive analytics, healthcare providers can optimize surgical decision-making, mitigate risks, and personalize treatment strategies to improve outcomes and ensure the highest standard of care for patients undergoing spine procedures. As technology continues to evolve, the future of spine surgery lies in harnessing the power of machine learning to transform patient safety and revolutionize surgical practices. The present review article was designed to discuss the available literature in the field of machine learning techniques to enhance patient safety in spine surgery. 

pdf/the-value-of-machine-learning-technology-and-artificial-1hfj90yrov.pdf

The value of machine learning technology and artificial intelligence to enhance patient safety in spine surgery: a review

A Bibliometric Analysis of Patient-Reported Outcome Measures in Adult Spinal Deformity, and the Future of Patient-Centric Outcome Assessments in the Era of Predictive Analytics

Adult spinal deformity (ASD) poses significant challenges in spinal surgery, requiring precise planning and execution for successful correction. Additionally, optimization of outcomes and reducing the high complication rates of ASD surgeries are additional challenges facing spinal deformity surgeons. The advent of machine learning (ML) has revolutionized various aspects of healthcare, including spinal surgery. This review provides a comprehensive overview of the current state of ML applications in spinal deformity corrective surgery, highlighting its potential benefits and challenges. 

Machine learning applications in adult spinal deformity corrective surgery: a narrative review

Identification of Barriers to AI Implementation in Medical Information Systems

The Emerging Role of Artificial Intelligence in Adult Spinal Deformity

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The Emerging Role of Artificial Intelligence in Adult Spinal Deformity