Orthopedic surgeons use machine learning to predict better patient outcomes and reduce costs

How is machine learning helping orthopedic surgeons predict better outcomes for patients? And how can those algorithms help predict how bone fracture surgery is approached? We will get those answers and much more on this episode with Dr. Akash Shah, Resident Physician in the Department of Orthopaedic Surgery at UCLA Medical Center. Dr. Shah received his Bachelor of Science at Duke University, and he went on to graduate from Harvard Medical School. He is also part of the team in the Department of Orthopaedic Surgery at the University of California, Los Angeles, that is working with international collaborators to build advanced machine learning (ML) models for hip and long bone fractures research. Dr. Shah and team received a grant from Oracle for Research to advance their research using Oracle Cloud to run high-powered ML models. Learn more about how Oracle for Research can help you speed up your research with grants, cloud computing, and hands-on support and expertise: www.oracle.com/research  

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"Research in Action" explores the dynamic world of life sciences, covering drug discovery, clinical trials, therapeutic development, and the pivotal role of real-world data and technology in connecting clinical research with patient care. Hear insightful conversations with scientists, clinicians, and leaders from pharma, biotech, and health.