Comparing three machine learning approaches to design a risk assessment tool for future fractures: predicting a subsequent major osteoporotic fracture in fracture patients with osteopenia and osteoporosis.

B C S de Vries Johannes H Hegeman Wieke S Nijmeijer Jeroen Geerdink Christin Seifert Catharina G M Groothuis-Oudshoorn

Published in: Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA (2021)

We show that predicting the risk of MOF in patients who already sustained a fracture can be done with adequate discriminative performance. We developed a user-friendly tool for risk calculation of subsequent MOF in patients with osteopenia.

Keyphrases

risk assessment
machine learning
bone mineral density
hip fracture
metal organic framework
postmenopausal women
heavy metals
artificial intelligence
current status
human health
deep learning
monte carlo