End-to-end learning of dynamical systems with black-box models, such as
...
The growth of machine learning as a field has been accelerating with
inc...
While much of the causal inference literature has focused on addressing
...
Difficulty in identifying cancer stage in health care claims data has li...
Risk adjustment in health care aims to redistribute payments to insurers...
We consider an extension of Leo Breiman's thesis from "Statistical Model...
When assessing causal effects, determining the target population to whic...
The use of machine learning (ML) in health care raises numerous ethical
...
The distribution of health care payments to insurance plans has substant...
Observational cohort studies with oversampled exposed subjects are typic...
Percutaneous coronary interventions (PCIs) are nonsurgical procedures to...
While risk adjustment is pervasive in the health care system, relatively...