MACHINE LEARNING + SPINE SURGERY
Jason Moore, PhD, MA, MS
Chair, Department of Computational Biomedicine
Professor of Computational Biomedicine and Medicine
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Corey Walker, MD
Assistant Professor of Neurosurgery
Cedars-Sinai spine surgeons, in collaboration with the Department of Computational Biomedicine, have made exciting progress in their machine-learning algorithms to predict post-surgical pain duration, medication dependency, readmission rates and other key outcomes in spine surgery. With time, their study—which uses thousands of variables—could give patients personalized predictions of their long-term pain levels and function before they make a decision about surgery.
"We’re building a machine-learning algorithm that integrates dozens of different data sources on genes, drugs, diseases, symptoms and more. It relies on insights from clinicians about what outcomes matter and how to interpret and use them to improve clinical care."
— Jason Moore, PhD, MA, MS
"When patients come here, they’re getting not only the best in technology, but also the highest level of accurate decision-making."
— Corey Walker, MD
Do No Harm, Enhance Practice
Every collaboration between Cedars-Sinai’s artificial intelligence experts and surgeons aims to preserve the ultimate goal of medicine—do no harm—while enhancing its practice. In this case, that means not only identifying who may require support weaning from opioids, but also facilitating more intensive intervention to assist patients at greatest risk of suboptimal outcomes.
Applying this knowledge to proactively provide support services is at the heart of the collaboration’s mission. The team’s constant focus on maintaining the patient as our No. 1 priority ensures that computer-based calculations are just one consideration among the broader scope of clinical care.
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Artificial intelligence tools help spine surgeons predict patient outcomes and address medication issues before they arise.
BROADCASTMED