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The ensemble artificial intelligence (AI) method: Detection of hip fractures in AP pelvis plain radiographs by majority voting using a multi-center dataset.

Salih BeyazSahika Betul YayliErsin KılıcUgur Doktur
Published in: Digital health (2023)
Our study demonstrates that the results obtained by aggregating the decisions of multiple models through voting, rather than relying solely on the decision of a single algorithm, are more consistent. The practical application of these algorithms will be difficult due to ethical, legal, and confidentiality issues, despite the theoretical success achieved. Developing successful algorithms and methodologies should not be viewed as the ultimate goal; it is important to understand how these algorithms will be used in real-life situations. In order to achieve more consistent results, feedback from clinical practice will be helpful.
Keyphrases
  • artificial intelligence
  • machine learning
  • deep learning
  • big data
  • clinical practice
  • convolutional neural network
  • decision making
  • transcription factor
  • total hip arthroplasty
  • quantum dots