131 citations · 180 across the 9 of their papers we have counts for
10 papers
Prompt engineering paradigms for medical applications: scoping review and recommendations for better practices
Jamil Zaghir, Marco Naguib, Mina Bjelogrlic +3
Prompt engineering is crucial for harnessing the potential of large language models (LLMs), especially in the medical domain where specialized terminology and phrasing is used. How…
A Benchmark Evaluation of Clinical Named Entity Recognition in French
Nesrine Bannour, Christophe Servan, Aurélie Névéol +1
Background: Transformer-based language models have shown strong performance on many Natural LanguageProcessing (NLP) tasks. Masked Language Models (MLMs) attract sustained interest…
Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting
Marco Naguib, Xavier Tannier, Aurélie Névéol
Large language models (LLMs) have become the preferred solution for many natural language processing tasks. In low-resource environments such as specialized domains, their few-shot…
Development and validation of a natural language processing algorithm to pseudonymize documents in the context of a clinical data warehouse
Xavier Tannier, Perceval Wajsbürt, Alice Calliger +4
The objective of this study is to address the critical issue of de-identification of clinical reports in order to allow access to data for research purposes, while ensuring patient…
Good practices for clinical data warehouse implementation: a case study in France
Matthieu Doutreligne, Adeline Degremont, Pierre-Alain Jachiet +2
Real World Data (RWD) bears great promises to improve the quality of care. However, specific infrastructures and methodologies are required to derive robust knowledge and brings in…
Effect of depth order on iterative nested named entity recognition models
Perceval Wajsburt, Yoann Taillé, Xavier Tannier
This paper studies the effect of the order of depth of mention on nested named entity recognition (NER) models. NER is an essential task in the extraction of biomedical information…
Terminologies augmented recurrent neural network model for clinical named entity recognition
Ivan Lerner, Nicolas Paris, Xavier Tannier
We aimed to enhance the performance of a supervised model for clinical named-entity recognition (NER) using medical terminologies. In order to evaluate our system in French, we bui…
Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata
Charlotte Rudnik, Thibault Ehrhart, Olivier Ferret +3
News agencies produce thousands of multimedia stories describing events happening in the world that are either scheduled such as sports competitions, political summits and election…
Hybrid Approaches for our Participation to the n2c2 Challenge on Cohort Selection for Clinical Trials
Xavier Tannier, Nicolas Paris, Hugo Cisneros +10
Objective: Natural language processing can help minimize human intervention in identifying patients meeting eligibility criteria for clinical trials, but there is still a long way…
Evaluating Temporal Graphs Built from Texts via Transitive Reduction
Xavier Tannier, Philippe Muller
Temporal information has been the focus of recent attention in information extraction, leading to some standardization effort, in particular for the task of relating events in a te…