Work

Boosting predictions of treatment success

Year: 2010

Type: article

Abstract: Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans the biological, physical, and social sciences.

Source: Proceedings of the National Academy of Sciences

DOI: 10.1073/pnas.1008052107

Authors: Michael LeBlanc, Charles Kooperberg

Institution: Fred Hutch Cancer Center

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: National Institutes of Health, National Cancer Institute