3 papers
cs.LG2024
Step-by-Step Guidance to Differential Anemia Diagnosis with Real-World Data and Deep Reinforcement Learning
Lillian Muyama, Estelle Lu, Geoffrey Cheminet +5
Clinical diagnostic guidelines outline the key questions to answer to reach a diagnosis. Inspired by guidelines, we aim to develop a model that learns from electronic health record…
cs.CL2024
Facilitating phenotyping from clinical texts: the medkit library
Antoine Neuraz, Ghislain Vaillant, Camila Arias +8
Phenotyping consists in applying algorithms to identify individuals associated with a specific, potentially complex, trait or condition, typically out of a collection of Electronic…
cs.LG2024
Deep Reinforcement Learning for Personalized Diagnostic Decision Pathways Using Electronic Health Records: A Comparative Study on Anemia and Systemic Lupus Erythematosus
Lillian Muyama, Antoine Neuraz, Adrien Coulet
Background: Clinical diagnosis is typically reached by following a series of steps recommended by guidelines authored by colleges of experts. Accordingly, guidelines play a crucial…