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Brett K. Beaulieu-Jones
Researcher at Harvard University
Publications - 59
Citations - 3393
Brett K. Beaulieu-Jones is an academic researcher from Harvard University. The author has contributed to research in topics: Medicine & Deep learning. The author has an hindex of 16, co-authored 47 publications receiving 2147 citations. Previous affiliations of Brett K. Beaulieu-Jones include Brigham and Women's Hospital & Beth Israel Deaconess Medical Center.
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Journal ArticleDOI
Opportunities and obstacles for deep learning in biology and medicine.
Travers Ching,Daniel Himmelstein,Brett K. Beaulieu-Jones,Alexandr A. Kalinin,Brian T. Do,Gregory P. Way,Enrico Ferrero,Paul-Michael Agapow,Michael Zietz,Michael M. Hoffman,Michael M. Hoffman,Wei Xie,Gail L. Rosen,Benjamin J. Lengerich,Johnny Israeli,Jack Lanchantin,Stephen Woloszynek,Anne E. Carpenter,Avanti Shrikumar,Jinbo Xu,Evan M. Cofer,Evan M. Cofer,Christopher A. Lavender,Srinivas C. Turaga,Amr Alexandari,Zhiyong Lu,David J. Harris,Dave DeCaprio,Yanjun Qi,Anshul Kundaje,Yifan Peng,Laura K. Wiley,Marwin H. S. Segler,Simina M. Boca,S. Joshua Swamidass,Austin Huang,Anthony Gitter,Anthony Gitter,Casey S. Greene +38 more
TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.
Journal ArticleDOI
Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing.
Brett K. Beaulieu-Jones,Zhiwei Steven Wu,Christopher J. Williams,Ran Lee,Sanjeev P. Bhavnani,James Brian Byrd,Casey S. Greene +6 more
TL;DR: This research presents a novel probabilistic approach that allows us to assess the importance of knowing the carrier and removal status of canine coronavirus, as a source of infection for other animals.
Journal ArticleDOI
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist
Beau Norgeot,Giorgio Quer,Brett K. Beaulieu-Jones,Ali Torkamani,Raquel Dias,Milena A. Gianfrancesco,Rima Arnaout,Isaac S. Kohane,Suchi Saria,Eric J. Topol,Ziad Obermeyer,Bin Yu,Atul J. Butte +12 more
TL;DR: The MI-CLAIM checklist is presented, a tool intended to improve transparent reporting of AI algorithms in medicine and to improve transparency in the evaluation of algorithms used in medicine.
Posted ContentDOI
Privacy-preserving generative deep neural networks support clinical data sharing
TL;DR: Deep neural networks are trained that generate synthetic subjects closely resembling study participants and incorporate differential privacy, which offers strong guarantees on the likelihood that a subject could be identified as a member of the trial while preserving the privacy of study participants.
Journal ArticleDOI
Semi-supervised learning of the electronic health record for phenotype stratification.
TL;DR: A semi-supervised learning method for EHR phenotype extraction using denoising autoencoders for phenotype stratification and a promising approach to clarify disease subtypes and improve genotype-phenotype association studies that leverage EHRs are developed.