Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Prasad Patil

Showing results (1-10 of 45) with videos related to

Pageof 5
Sort By:
Proceedings of the National Academy of Sciences of the United States of America|March 14, 2018
Training replicable predictors in multiple studiesPrasad Patil, Giovanni Parmigiani
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 5, 2019
Tree-Weighting for Multi-Study Ensemble LearnersMaya Ramchandran, Prasad Patil, Giovanni Parmigiani
Bioinformatics (Oxford, England)|December 28, 2022
A pairwise strategy for imputing predictive features when combining multiple datasetsYujie Wu, Boyu Ren, Prasad Patil
Perspectives on Psychological Science : a Journal of the Association for Psychological Science|July 31, 2016
What Should Researchers Expect When They Replicate Studies? A Statistical View of Replicability in Psychological SciencePrasad Patil, Roger D Peng, Jeffrey T Leek
Nature Human Behaviour|June 19, 2019
A visual tool for defining reproducibility and replicabilityPrasad Patil, Roger D Peng, Jeffrey T Leek
Nature Human Behaviour|July 31, 2019
Publisher Correction: A visual tool for defining reproducibility and replicabilityPrasad Patil, Roger D Peng, Jeffrey T Leek
Biostatistics (Oxford, England)|December 18, 2025
Multi-study R-learner for estimating heterogeneous treatment effects across studies using statistical machine learningCathy Shyr, Boyu Ren, Prasad Patil, et al.
Contemporary Clinical Trials Communications|May 9, 2018
Genomic and clinical predictors for improving estimator precision in randomized trials of breast cancer treatmentsPrasad Patil, Elizabeth Colantuoni, Jeffrey T Leek, et al.
Bioinformatics (Oxford, England)|November 27, 2020
Robustifying genomic classifiers to batch effects via ensemble learningYuqing Zhang, Prasad Patil, W Evan Johnson, et al.
The Annals of Applied Statistics|October 24, 2022
Hierarchical resampling for bagging in multistudy prediction with applications to human neurochemical sensingGabriel Loewinger, Prasad Patil, Kenneth T Kishida, et al.
Pageof 5

Showing results (1-10 of 45) with videos related to

Sort By:
Pageof 5
Proceedings of the National Academy of Sciences of the United States of America|March 14, 2018
Training replicable predictors in multiple studiesPrasad Patil, Giovanni Parmigiani
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 5, 2019
Tree-Weighting for Multi-Study Ensemble LearnersMaya Ramchandran, Prasad Patil, Giovanni Parmigiani
Bioinformatics (Oxford, England)|December 28, 2022
A pairwise strategy for imputing predictive features when combining multiple datasetsYujie Wu, Boyu Ren, Prasad Patil
Perspectives on Psychological Science : a Journal of the Association for Psychological Science|July 31, 2016
What Should Researchers Expect When They Replicate Studies? A Statistical View of Replicability in Psychological SciencePrasad Patil, Roger D Peng, Jeffrey T Leek
Nature Human Behaviour|June 19, 2019
A visual tool for defining reproducibility and replicabilityPrasad Patil, Roger D Peng, Jeffrey T Leek
Nature Human Behaviour|July 31, 2019
Publisher Correction: A visual tool for defining reproducibility and replicabilityPrasad Patil, Roger D Peng, Jeffrey T Leek
Biostatistics (Oxford, England)|December 18, 2025
Multi-study R-learner for estimating heterogeneous treatment effects across studies using statistical machine learningCathy Shyr, Boyu Ren, Prasad Patil, et al.
Contemporary Clinical Trials Communications|May 9, 2018
Genomic and clinical predictors for improving estimator precision in randomized trials of breast cancer treatmentsPrasad Patil, Elizabeth Colantuoni, Jeffrey T Leek, et al.
Bioinformatics (Oxford, England)|November 27, 2020
Robustifying genomic classifiers to batch effects via ensemble learningYuqing Zhang, Prasad Patil, W Evan Johnson, et al.
The Annals of Applied Statistics|October 24, 2022
Hierarchical resampling for bagging in multistudy prediction with applications to human neurochemical sensingGabriel Loewinger, Prasad Patil, Kenneth T Kishida, et al.
Pageof 5