Evicase: An evidence-based case structuring approach for personalized healthcare

Carmeli, Boaz; Casali, Paolo; Goldbraich, Anna; Goldsteen, Abigail; Kent, Carmel; Licitra, Lisa; Locatelli, Paolo; Restifo, Nicola; Rinott, Ruty; Sini, Elena; Torresani, Michele and Waks, Zeev In: Mantas, John; Andersen, Stig Kjær; Mazzoleni, Maria Christina; Blobel, Bernd; Quaglini, Silvana and Moen, Anne eds. Quality of Life through Quality of Information. Studies in Health Technology and Informatics, 180. IOS Press, pp. 604–608.

DOI: https://doi.org/10.3233/978-1-61499-101-4-604

Abstract

The personalized medicine era stresses a growing need to combine evidence-based medicine with case based reasoning in order to improve the care process. To address this need we suggest a framework to generate multi-tiered statistical structures we call Evicases. Evicase integrates established medical evidence together with patient cases from the bedside. It then uses machine learning algorithms to produce statistical results and aggregators, weighted predictions, and appropriate recommendations. Designed as a stand-alone structure, Evicase can be used for a range of decision support applications including guideline adherence monitoring and personalized prognostic predictions. ? 2012 European Federation for Medical Informatics and IOS Press. All rights reserved.

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About

  • Item ORO ID
  • 80179
  • Item Type
  • Book Section
  • ISBN
  • 1879-8365
  • Keywords
  • Decision Support; Personalized Medicine; Clinical Guidelines; Clinical Business Intelligence; Machine-Learning Algorithms
  • Academic Unit or School
  • Faculty of Wellbeing, Education and Language Studies (WELS)
  • Copyright Holders
  • © 2021 IOS Press
  • Depositing User
  • Carmel Kent

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