Characterization and comparison of clinical pathways extracted from electronic health records



Main objectives

The ShareFAIR project aims to learn pathways from clinical data collected throughout the healthcare activity in electronic medical records (EMRs) in order to explain
(i) medical decision-making processes (steps in arriving at a particular diagnosis or therapeutic choice) and (ii) steps in disease management.

ShareFAIR is a PEPR Santé Numérique project funded as part of the France 2030 program, reference ANR-22-PESN-0007.


The ShareFAIR project investigates the possibility of learning recommendations for medical diagnoses or routes to a clinical decision from electronic medical records, and thus covering special cases not covered by good practice guidelines, adapting them to emerging practices, and generally enabling theory and practice to be compared.

Methodology/Technology used

(1) Validation of methods and tools for data-driven protocol learning based on implementations previously developed in the HeKA team. (2) Representation of learned protocols with FAIR standards via the definition of a common framework for clinical protocol representation, drawing on the ShareFAIR project consortium's experience in scientific workflow and open science. (3) Comparison of clinical pathways, associated with the same clinical framework. Translated with (free version)



Adrien Coulet () & Antoine Neuraz () & Bastien Rance ()


Inria, AP-HP, Inserm, Université Paris Cité

Useful links

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Names of partners involved
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