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

BCMA-ES II: revisiting Bayesian CMA-ES

no code implementations • 2 Apr 2019 • Eric Benhamou, David Saltiel, Beatrice Guez, Nicolas Paris

We prove that the expected covariance should be lower in the normal Wishart prior model because of the convexity of the inverse.

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.

Evaluation of a Sequence Tagging Tool for Biomedical Texts

1 code implementation • WS 2018 • Julien Tourille, Matthieu Doutreligne, Olivier Ferret, Aur{\'e}lie N{\'e}v{\'e}ol, Nicolas Paris, Xavier Tannier

Many applications in biomedical natural language processing rely on sequence tagging as an initial step to perform more complex analysis.

named-entity-recognition Named Entity Recognition +4

Solving WCSP by Extraction of Minimal Unsatisfiable Cores

no code implementations • 19 Apr 2013 • Christophe Lecoutre, Nicolas Paris, Olivier Roussel, Sébastien Tabary

Usual techniques to solve WCSP are based on cost transfer operations coupled with a branch and bound algorithm.