18 citations · 34 across the 6 of their papers we have counts for
10 papers
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression
Zhaozhi Qian, William R. Zame, Lucas M. Fleuren +2
Modeling a system's temporal behaviour in reaction to external stimuli is a fundamental problem in many areas. Pure Machine Learning (ML) approaches often fail in the small sample…
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups
Hyun-Suk Lee, Cong Shen, William Zame +2
Phase I clinical trials are designed to test the safety (non-toxicity) of drugs and find the maximum tolerated dose (MTD). This task becomes significantly more challenging when mul…
Learning outside the Black-Box: The pursuit of interpretable models
Jonathan Crabbé, Yao Zhang, William Zame +1
Machine Learning has proved its ability to produce accurate models but the deployment of these models outside the machine learning community has been hindered by the difficulties o…
AutoCP: Automated Pipelines for Accurate Prediction Intervals
Yao Zhang, William Zame, Mihaela van der Schaar
Successful application of machine learning models to real-world prediction problems, e.g. financial forecasting and personalized medicine, has proved to be challenging, because suc…
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification
Hyun-Suk Lee, Yao Zhang, William Zame +3
Subgroup analysis of treatment effects plays an important role in applications from medicine to public policy to recommender systems. It allows physicians (for example) to identify…
Adaptive Clinical Trials: Exploiting Sequential Patient Recruitment and Allocation
Onur Atan, William R. Zame, Mihaela van der Schaar
Randomized Controlled Trials (RCTs) are the gold standard for comparing the effectiveness of a new treatment to the current one (the control). Most RCTs allocate the patients to th…