Improving the accuracy of medical diagnosis with causal machine learning
JG Richens, CM Lee, S Johri - Nature communications, 2020 - nature.com
Abstract Machine learning promises to revolutionize clinical decision making and diagnosis.
In medical diagnosis a doctor aims to explain a patient's symptoms by determining the …
In medical diagnosis a doctor aims to explain a patient's symptoms by determining the …
Simulation intelligence: Towards a new generation of scientific methods
A Lavin, D Krakauer, H Zenil, J Gottschlich… - ar** datasets using bivariate causal discovery
Causal knowledge is vital for effective reasoning in science, as causal relations, unlike
correlations, allow one to reason about the outcomes of interventions. Algorithms that can …
correlations, allow one to reason about the outcomes of interventions. Algorithms that can …
Disentangling causal effects from sets of interventions in the presence of unobserved confounders
O Jeunen, C Gilligan-Lee… - Advances in Neural …, 2022 - proceedings.neurips.cc
The ability to answer causal questions is crucial in many domains, as causal inference
allows one to understand the impact of interventions. In many applications, only a single …
allows one to understand the impact of interventions. In many applications, only a single …
A language for counterfactual generative models
We present Omega, a probabilistic programming language with support for counterfactual
inference. Counterfactual inference means to observe some fact in the present, and infer …
inference. Counterfactual inference means to observe some fact in the present, and infer …