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Elias Chaibub Neto

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Scientific Reports|November 22, 2016
Using instrumental variables to disentangle treatment and placebo effects in blinded and unblinded randomized clinical trials influenced by unmeasured confoundersElias Chaibub Neto
IEEE Transactions on Neural Networks and Learning Systems|September 14, 2022
Causality-Aware Predictions in Static Anticausal Machine Learning TasksElias Chaibub Neto
Plos One|July 1, 2015
Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size ApplicationsElias Chaibub Neto
Clinical Pharmacology and Therapeutics|February 10, 2020
Data Science Approaches for Effective Use of Mobile Device-Based Collection of Real-World DataLarsson Omberg, Elias Chaibub Neto, Lara M Mangravite
Plos One|October 8, 2014
Simulation studies as designed experiments: the comparison of penalized regression models in the "large p, small n" settingElias Chaibub Neto, J Christopher Bare, Adam A Margolin
BMC Medical Informatics and Decision Making|February 20, 2024
A novel estimator for the two-way partial AUCElias Chaibub Neto, Vijay Yadav, Solveig K Sieberts, et al.
Interactive Journal of Medical Research|March 19, 2025
Long-Term Engagement of Diverse Study Cohorts in Decentralized Research: Longitudinal Analysis of "All of Us" Research Program DataVijay Yadav, Elias Chaibub Neto, Megan Doerr, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 4, 2013
The Stream algorithm: computationally efficient ridge-regression via Bayesian model averaging, and applications to pharmacogenomic prediction of cancer cell line sensitivityElias Chaibub Neto, In Sock Jang, Stephen H Friend, et al.
Genetics|May 29, 2008
Inferring causal phenotype networks from segregating populationsElias Chaibub Neto, Christine T Ferrara, Alan D Attie, et al.
The Annals of Applied Statistics|January 11, 2011
CAUSAL GRAPHICAL MODELS IN SYSTEMS GENETICS: A UNIFIED FRAMEWORK FOR JOINT INFERENCE OF CAUSAL NETWORK AND GENETIC ARCHITECTURE FOR CORRELATED PHENOTYPESElias Chaibub Neto, Mark P Keller, Alan D Attie, et al.
Pageof 5

Showing results (1-10 of 41) with videos related to

Sort By:
Pageof 5
Scientific Reports|November 22, 2016
Using instrumental variables to disentangle treatment and placebo effects in blinded and unblinded randomized clinical trials influenced by unmeasured confoundersElias Chaibub Neto
IEEE Transactions on Neural Networks and Learning Systems|September 14, 2022
Causality-Aware Predictions in Static Anticausal Machine Learning TasksElias Chaibub Neto
Plos One|July 1, 2015
Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size ApplicationsElias Chaibub Neto
Clinical Pharmacology and Therapeutics|February 10, 2020
Data Science Approaches for Effective Use of Mobile Device-Based Collection of Real-World DataLarsson Omberg, Elias Chaibub Neto, Lara M Mangravite
Plos One|October 8, 2014
Simulation studies as designed experiments: the comparison of penalized regression models in the "large p, small n" settingElias Chaibub Neto, J Christopher Bare, Adam A Margolin
BMC Medical Informatics and Decision Making|February 20, 2024
A novel estimator for the two-way partial AUCElias Chaibub Neto, Vijay Yadav, Solveig K Sieberts, et al.
Interactive Journal of Medical Research|March 19, 2025
Long-Term Engagement of Diverse Study Cohorts in Decentralized Research: Longitudinal Analysis of "All of Us" Research Program DataVijay Yadav, Elias Chaibub Neto, Megan Doerr, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 4, 2013
The Stream algorithm: computationally efficient ridge-regression via Bayesian model averaging, and applications to pharmacogenomic prediction of cancer cell line sensitivityElias Chaibub Neto, In Sock Jang, Stephen H Friend, et al.
Genetics|May 29, 2008
Inferring causal phenotype networks from segregating populationsElias Chaibub Neto, Christine T Ferrara, Alan D Attie, et al.
The Annals of Applied Statistics|January 11, 2011
CAUSAL GRAPHICAL MODELS IN SYSTEMS GENETICS: A UNIFIED FRAMEWORK FOR JOINT INFERENCE OF CAUSAL NETWORK AND GENETIC ARCHITECTURE FOR CORRELATED PHENOTYPESElias Chaibub Neto, Mark P Keller, Alan D Attie, et al.
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