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The Importance of Nonlinear Transformations Use in Medical Data Analysis.

Netta ShacharAlexis MitelpunktTal KozlovskiTal GaliliTzviel FrostigBarak BrillMira Markus-KalishYoav Benjamini
Published in: JMIR medical informatics (2018)
This work presents the use of nonlinear transformations for medical data and the importance of their semi-automated choice. Using the described approach, the data analyst increases the ability to create simpler, more robust and translational models, thereby facilitating the interpretation and implementation of the analysis by medical practitioners. Applying nonlinear transformations as part of the preprocessing is essential to the quality and interpretability of results.
Keyphrases
  • data analysis
  • healthcare
  • primary care
  • electronic health record
  • big data
  • machine learning
  • deep learning
  • high throughput
  • single cell