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AI-based hip prosthesis failure prediction through evolutional radiological indices.

Matteo BulloniFrancesco Manlio GambaroKatia ChiappettaGuido GrappioloValentina CorinoMattia Loppini
Published in: Archives of orthopaedic and trauma surgery (2023)
The proposed predictor may represent a highly sensitive screening tool for clinicians, capable to predict THA failure with an advance between a few months and more than a year through only four radiological parameters, considering either their value at the latest visit or their evolution through time.
Keyphrases
  • artificial intelligence
  • palliative care
  • machine learning
  • mass spectrometry
  • molecularly imprinted
  • deep learning
  • label free
  • tandem mass spectrometry