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Prediction of Perforated and Nonperforated Acute Appendicitis Using Machine Learning-Based Explainable Artificial Intelligence.

Sami AkbulutFatma Hilal YagınIpek Balikci CicekCemalettin KocCemil ÇolakSezai Yilmaz
Published in: Diagnostics (Basel, Switzerland) (2023)
For the first time in the literature, a new approach combining ML and XAI methods was tried to predict AAp and perforated AAp, and both clinical conditions were predicted with high accuracy. This new approach proved successful in showing how well which demographic and biochemical parameters could explain the current clinical situation in predicting AAp and perforated AAp.
Keyphrases
  • artificial intelligence
  • machine learning
  • big data
  • deep learning
  • systematic review