Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Risk Prediction of Low Bone Density in Elderly Patients with Supervised Machine Learning Algorithms
0
Zitationen
2
Autoren
2025
Jahr
Abstract
Tree-based ML models, particularly Extra Trees, can effectively predict low BMD. The identified risk factors include both established and lesser-studied predictors. These findings support the use of ML for personalized osteoporosis and osteopenia screening and highlight its ability to capture complex, multifactorial relationships in population health data.
Ähnliche Arbeiten
Vitamin D Deficiency
2007 · 13.428 Zit.
Evaluation, Treatment, and Prevention of Vitamin D Deficiency: an Endocrine Society Clinical Practice Guideline
2011 · 10.295 Zit.
How useful is SBF in predicting in vivo bone bioactivity?
2006 · 9.312 Zit.
Osteoporosis Prevention, Diagnosis, and Therapy
2001 · 5.453 Zit.
An estimate of the worldwide prevalence and disability associated with osteoporotic fractures
2006 · 4.603 Zit.