3 citations · 6 across the 5 of their papers we have counts for
5 papers
Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration
Alexandre Perez-Lebel, Gael Varoquaux, Sanmi Koyejo +2
Probabilistic classifiers are central for making informed decisions under uncertainty. Based on the maximum expected utility principle, optimal decision rules can be derived using…
Causal thinking for decision making on Electronic Health Records: why and how
Matthieu Doutreligne, Tristan Struja, Judith Abecassis +3
Accurate predictions, as with machine learning, may not suffice to provide optimal healthcare for every patient. Indeed, prediction can be driven by shortcuts in the data, such as…
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…
How to select predictive models for causal inference?
Matthieu Doutreligne, Gaël Varoquaux
As predictive models -- e.g., from machine learning -- give likely outcomes, they may be used to reason on the effect of an intervention, a causal-inference task. The increasing co…
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…