33 citations · 122 across the 12 of their papers we have counts for
4 papers · 1 filter
Instability in clinical risk stratification models using deep learning
Daniel Lopez-Martinez, Alex Yakubovich, Martin Seneviratne +9
While it has been well known in the ML community that deep learning models suffer from instability, the consequences for healthcare deployments are under characterised. We study th…
Clinical Utility Gains from Incorporating Comorbidity and Geographic Location Information into Risk Estimation Equations for Atherosclerotic Cardiovascular Disease
Yizhe Xu, Agata Foryciarz, Ethan Steinberg +1
Objective: There are several efforts to re-learn the 2013 ACC/AHA pooled cohort equations (PCE) for patients with specific comorbidities and geographic locations. With over 363 cus…
Treatment Heterogeneity for Survival Outcomes
Yizhe Xu, Nikolaos Ignatiadis, Erik Sverdrup +3
Estimation of conditional average treatment effects (CATEs) plays an essential role in modern medicine by informing treatment decision-making at a patient level. Several metalearne…
Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare
Stephen R. Pfohl, Yizhe Xu, Agata Foryciarz +3
A growing body of work uses the paradigm of algorithmic fairness to frame the development of techniques to anticipate and proactively mitigate the introduction or exacerbation of h…