https://www.selleckchem.com/pr....oducts/Fasudil-HCl(H
This paper proposes the use of ML models to assess and predict hip fracture risk. Clinical, geometric, and biomechanical variables from the finite element simulation of a side fall are used as independent variables to train the models. Among the different tested models, Random Forest stands out, showing its capability to outperform BMD-DXA, achieving an accuracy over 87%, with specificity over 92% and sensitivity over 83%.In the process of artificial interventional therapy, the operation of artificial catheter is not accura
Like
Comment
Share
