Abstract:Introduction:
Low-energy proximal femur fractures in elderly patients result from factors, like osteoporosis and falls. These fractures impose high rates of economic and social costs. In this study, we aimed to build predictive models by applying machine learning (ML) methods on radiomics features to predict low-energy proximal femur fractures.
background:
Low-energy proximal femur fractures in the elderly patients are resulted from factors like osteoporosis and falls. These fractures impose high rates of ec… Show more
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