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Abstract #1441

Measure for Measure: Machine Learning Models for Osteoporosis MRI data

Uran Ferizi1, Harrison Besser1, Chamith S Rajapakse2, Punam K Saha3, Stephen Honig1, and Gregory Chang1

1New York University School of Medicine, New York, NY, United States, 2University of Pennsylvania School of Medicine, Philadelphia, PA, United States, 3University of Iowa College of Medicine, Iowa City, IA, United States

We examine how Machine Learning can be used to identify novel risk factors of osteoporotic bone fracture. Using measurements from patient MRI scans at five anatomical sites, we sought to find which specific regions are best for stratifying the risk of osteoporotic fracture. Further studies on these models and other data will help improve clinicians’ ability to accurately diagnose Osteoporosis, so that patients at risk for bone fracture may be caught and treated earlier.

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