Literature DB >> 20656935

Boosting predictions of treatment success.

Michael LeBlanc1, Charles Kooperberg.   

Abstract

Mesh：

Year:  2010        PMID： 20656935      PMCID： PMC2922272          DOI： 10.1073/pnas.1008052107

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN： 0027-8424            Impact factor:   11.205


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  4 in total

1.  Deep phenotyping to predict live birth outcomes in in vitro fertilization.

Authors:  Prajna Banerjee; Bokyung Choi; Lora K Shahine; Sunny H Jun; Kathleen O'Leary; Ruth B Lathi; Lynn M Westphal; Wing H Wong; Mylene W M Yao
Journal:  Proc Natl Acad Sci U S A       Date:  2010-07-19       Impact factor: 11.205

2.  Structures and Assumptions: Strategies to Harness Gene × Gene and Gene × Environment Interactions in GWAS.

Authors:  Charles Kooperberg; Michael Leblanc; James Y Dai; Indika Rajapakse
Journal:  Stat Sci       Date:  2009       Impact factor: 2.901

3.  Extreme regression.

Authors:  Michael LeBlanc; James Moon; Charles Kooperberg
Journal:  Biostatistics       Date:  2005-06-22       Impact factor: 5.899

4.  Risk prediction using genome-wide association studies.

Authors:  Charles Kooperberg; Michael LeBlanc; Valerie Obenchain
Journal:  Genet Epidemiol       Date:  2010-11       Impact factor: 2.135
  4 in total
  1 in total

1.  Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Authors:  Adrien Badré; Li Zhang; Wellington Muchero; Justin C Reynolds; Chongle Pan
Journal:  J Hum Genet       Date:  2020-10-02       Impact factor: 3.172
  1 in total

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