2 papers
cs.LG2024
How Should We Represent History in Interpretable Models of Clinical Policies?
Anton Matsson, Lena Stempfle, Yaochen Rao +3
Modeling policies for sequential clinical decision-making based on observational data is useful for describing treatment practices, standardizing frequent patterns in treatment, an…
cs.LG2024
Handling missing values in clinical machine learning: Insights from an expert study
Lena Stempfle, Arthur James, Julie Josse +2
Inherently interpretable machine learning (IML) models offer valuable support for clinical decision-making but face challenges when features contain missing values. Traditional app…