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A Comparison of Decision Tree Algorithms in the Assessment of Biomedical Data.

Fahima HajjejManal Abdullah AlohaliMalek BadrMd Adnan Rahman
Published in: BioMed research international (2022)
By comparing the performance of various tree algorithms, we can determine which one is most useful for analyzing biomedical data. In artificial intelligence, decision trees are a classification model known for their visual aid in making decisions. WEKA software will evaluate biological data from real patients to see how well the decision tree classification algorithm performs. Another goal of this comparison is to assess whether or not decision trees can serve as an effective tool for medical diagnosis in general. In doing so, we will be able to see which algorithms are the most efficient and appropriate to use when delving into this data and arrive at an informed decision.
Keyphrases
  • machine learning
  • artificial intelligence
  • deep learning
  • big data
  • electronic health record
  • decision making
  • data analysis
  • healthcare
  • newly diagnosed
  • ejection fraction
  • patient reported outcomes