Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.

Wei- Chieh Hung Yih-Lon LinTien-Tsai ChengWei-Leng ChinLi-Te TuChih-Kui ChenChih-Hui Yang Chih-Hsing Wu

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 (2023)

While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of under- and over-treated patients when no BMD measurements were available. The validated models could be used to screen for patients at a high risk of fracture and osteoporosis.

Keyphrases

bone mineral density
postmenopausal women
deep learning
end stage renal disease
body composition
newly diagnosed
ejection fraction
chronic kidney disease
prognostic factors
peritoneal dialysis
polycystic ovary syndrome
patient reported outcomes
insulin resistance
breast cancer risk