Learning the grammar of drug prescription: recurrent neural network grammars for medication information extraction in clinical texts

no code implementations • 24 Apr 2020 • Ivan Lerner, Jordan Jouffroy, Anita Burgun, Antoine Neuraz

Similarly, we evaluated seq-RNNG, a hybrid RNNG model that takes as extra-input the output of the BiLSTMs for entities and events.

Event Detection Inductive Bias

Terminologies augmented recurrent neural network model for clinical named entity recognition

no code implementations • 25 Apr 2019 • Ivan Lerner, Nicolas Paris, Xavier Tannier

On APcNER corpus, the micro-average F-measure of the hybrid system on the 5 entities was 69. 5% in exact match, and 84. 1% in non-exact match.

named-entity-recognition Named Entity Recognition +1

Hybrid Approaches for our Participation to the n2c2 Challenge on Cohort Selection for Clinical Trials

no code implementations • 19 Mar 2019 • Xavier Tannier, Nicolas Paris, Hugo Cisneros, Christel Daniel, Matthieu Doutreligne, Catherine Duclos, Nicolas Griffon, Claire Hassen-Khodja, Ivan Lerner, Adrien Parrot, Éric Sadou, Cyrina Saussol, Pascal Vaillant

Materials and Methods: The first method is a weakly supervised method using an unlabeled corpus (MIMIC) to build a silver standard, by producing semi-automatically a small and very precise set of rules to detect some samples of positive and negative patients.