4 citations · 4 across the 4 of their papers we have counts for
4 papers
PARHAF, a human-authored corpus of clinical reports for fictitious patients in French
Xavier Tannier, Salam Abbara, Rémi Flicoteaux +4
The development of clinical natural language processing (NLP) systems is severely hampered by the sensitive nature of medical records, which restricts data sharing under stringent…
The Environmental Impacts of Machine Learning Training Keep Rising Evidencing Rebound Effect
Clément Morand, Anne-Laure Ligozat, Aurélie Névéol
Recent Machine Learning (ML) approaches have shown increased performance on benchmarks but at the cost of escalating computational demands. Hardware, algorithmic and carbon optimiz…
Efficient extraction of medication information from clinical notes: an evaluation in two languages
Thibaut Fabacher, Erik-André Sauleau, Emmanuelle Arcay +6
Objective: To evaluate the accuracy, computational cost and portability of a new Natural Language Processing (NLP) method for extracting medication information from clinical narrat…
How Green Can AI Be? A Study of Trends in Machine Learning Environmental Impacts
Clément Morand, Anne-Laure Ligozat, Aurélie Névéol
The compute requirements associated with training Artificial Intelligence (AI) models have increased exponentially over time. Optimisation strategies aim to reduce the energy consu…