Brett K. Beaulieu-Jones, PhD
Brett Beaulieu-Jones, PhD
Instructor in Biomedical Informatics, Harvard Medical School
Research Fellow in Neurology, Brigham and Women's Hospital
Biomedical Informatics Research Training Fellow, 2017-2019

Brett Beaulieu-Jones received his PhD from the Perelman School of Medicine at the University of Pennsylvania under the supervision of Dr. Jason Moore and Dr. Casey Greene. Beaulieu-Jones’ doctoral research focused on using machine learning-based methods to more precisely define phenotypes from large-scale biomedical data repositories, e.g. those contained in clinical records. At DBMI he is expanding this concentration to include large-scale data integration (genomic, therapeutic, imaging) to both better understand disease etiology as well as provide precise therapeutic recommendations. Initially, he is working to develop targeted models of drug selection for patients with refractory epilepsy and to further develop machine learning methods that model the way patients progress over time using longitudinal data.  

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.
Authors: Norgeot B, Quer G, Beaulieu-Jones BK, Torkamani A, Dias R, Gianfrancesco M, Arnaout R, Kohane IS, Saria S, Topol E, Obermeyer Z, Yu B, Butte AJ.
Nat Med
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Examining the Use of Real-World Evidence in the Regulatory Process.
Authors: Beaulieu-Jones BK, Finlayson SG, Yuan W, Altman RB, Kohane IS, Prasad V, Yu KH.
Clin Pharmacol Ther
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International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.
Authors: Brat GA, Weber GM, Gehlenborg N, Avillach P, Palmer NP, Chiovato L, Cimino J, Waitman LR, Omenn GS, Malovini A, Moore JH, Beaulieu-Jones BK, Tibollo V, Murphy SN, Yi SL, Keller MS, Bellazzi R, Hanauer DA, Serret-Larmande A, Gutierrez-Sacristan A, Holmes JJ, Bell DS, Mandl KD, Follett RW, Klann JG, Murad DA, Scudeller L, Bucalo M, Kirchoff K, Craig J, Obeid J, Jouhet V, Griffier R, Cossin S, Moal B, Patel LP, Bellasi A, Prokosch HU, Kraska D, Sliz P, Tan ALM, Ngiam KY, Zambelli A, Mowery DL, Schiver E, Devkota B, Bradford RL, Daniar M, Daniel C, Benoit V, Bey R, Paris N, Serre P, Orlova N, Dubiel J, Hilka M, Jannot AS, Breant S, Leblanc J, Griffon N, Burgun A, Bernaux M, Sandrin A, Salamanca E, Cormont S, Ganslandt T, Gradinger T, Champ J, Boeker M, Martel P, Esteve L, Gramfort A, Grisel O, Leprovost D, Moreau T, Varoquaux G, Vie JJ, Wassermann D, Mensch A, Caucheteux C, Haverkamp C, Lemaitre G, Bosari S, Krantz ID, South A, Cai T, Kohane IS.
NPJ Digit Med
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Packaging Biocomputing Software to Maximize Distribution and Reuse.
Authors: Bush WS, Wheeler N, Beaulieu-Jones B, Darabos C.
Pac Symp Biocomput
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Ongoing challenges and innovative approaches for recognizing patterns across large-scale, integrative biomedical datasets.
Authors: Kobren SN, Beaulieu-Jones B, Darabos C, Kim D, Verma A.
Pac Symp Biocomput
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Trends and Focus of Machine Learning Applications for Health Research.
Authors: Beaulieu-Jones B, Finlayson SG, Chivers C, Chen I, McDermott M, Kandola J, Dalca AV, Beam A, Fiterau M, Naumann T.
JAMA Netw Open
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Privacy-Preserving Generative Deep Neural Networks Support Clinical Data Sharing.
Authors: Beaulieu-Jones BK, Wu ZS, Williams C, Lee R, Bhavnani SP, Byrd JB, Greene CS.
Circ Cardiovasc Qual Outcomes
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Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes.
Authors: Beaulieu-Jones BK, Kohane IS, Beam AL.
Pac Symp Biocomput
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Opportunities and obstacles for deep learning in biology and medicine.
Authors: Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow PM, Zietz M, Hoffman MM, Xie W, Rosen GL, Lengerich BJ, Israeli J, Lanchantin J, Woloszynek S, Carpenter AE, Shrikumar A, Xu J, Cofer EM, Lavender CA, Turaga SC, Alexandari AM, Lu Z, Harris DJ, DeCaprio D, Qi Y, Kundaje A, Peng Y, Wiley LK, Segler MHS, Boca SM, Swamidass SJ, Huang A, Gitter A, Greene CS.
J R Soc Interface
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Characterizing and Managing Missing Structured Data in Electronic Health Records: Data Analysis.
Authors: Beaulieu-Jones BK, Lavage DR, Snyder JW, Moore JH, Pendergrass SA, Bauer CR.
JMIR Med Inform
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