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Osteoporotic hip fracture prediction from risk factors available in administrative claims data - A machine learning approach.

Hans-Helmut KönigKatrin C ReberIvonne LindlbauerKilian RappGisela BücheleJochen KlenkAndreas Daniel MeidClemens BeckerHans-Helmut König
Published in: PloS one (2020)
The superlearner achieved similar predictive performance compared to the individual algorithms included. Nevertheless, in the presence of non-linearity and complex interactions, this method might be a flexible alternative to be considered for risk prediction in large datasets.
Keyphrases
  • hip fracture
  • machine learning
  • risk factors
  • big data
  • artificial intelligence
  • health insurance
  • electronic health record
  • deep learning
  • bone mineral density
  • data analysis
  • postmenopausal women