335 citations · 347 across the 4 of their papers we have counts for
5 papers · 1 filter
OncoSynth: Synthetic data generation for treatment effect estimation in oncology
Octavia-Andreea Ciora, Julian Welzel, Dennis Frauen +6
In oncology, access to patient-level data is often restricted. Synthetic data provides an alternative for analyzing treatment effectiveness, but existing methods for synthetic data…
Causal machine learning for predicting treatment outcomes
Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk +7
Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of…
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge
Trent Kyono, Ioana Bica, Zhaozhi Qian +1
Selecting causal inference models for estimating individualized treatment effects (ITE) from observational data presents a unique challenge since the counterfactual outcomes are ne…
CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19
Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar
The coronavirus disease 2019 (COVID-19) global pandemic poses the threat of overwhelming healthcare systems with unprecedented demands for intensive care resources. Managing these…
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning
Ahmed M. Alaa, Mihaela van der Schaar
Clinical prognostic models derived from largescale healthcare data can inform critical diagnostic and therapeutic decisions. To enable off-theshelf usage of machine learning (ML) i…