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Evicase: An Evidence-based Case Structuring Approach for Personalized Healthcare
Boaz Carmeli, Paolo Casali, Anna Goldbraich, Abigail Goldsteen, Carmel Kent, Lisa Licitra, Paolo Locatelli, Nicola Restifo, Ruty Rinott, Elena Sini, Michele Torresani, Zeev Waks
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.
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