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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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Opportunities and obstacles for deep learning in biology and medicine.

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.
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Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing.

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.
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Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist

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.
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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.