32 citations · 42 across the 5 of their papers we have counts for
3 papers · 1 filter
Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression
Alexander Norcliffe, Lev Proleev, Diana Mincu +3
Multiple sclerosis is a disease that affects the brain and spinal cord, it can lead to severe disability and has no known cure. The majority of prior work in machine learning for m…
Boosting the interpretability of clinical risk scores with intervention predictions
Eric Loreaux, Ke Yu, Jonas Kemp +8
Machine learning systems show significant promise for forecasting patient adverse events via risk scores. However, these risk scores implicitly encode assumptions about future inte…
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo +14
Diagnosing and mitigating changes in model fairness under distribution shift is an important component of the safe deployment of machine learning in healthcare settings. Importantl…