Brett K. Beaulieu-Jones, PhD

Brett Beaulieu-Jones, PhD

Former Instructor in Biomedical Informatics
Former Research Fellow in Neurology, Brigham and Women's Hospital
Biomedical Informatics Research Training Fellow, 2017-2019
Zaklab (Kohane)

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.  

Accelerating diagnosis of Parkinson's disease through risk prediction.
Authors: Yuan W, Beaulieu-Jones B, Krolewski R, Palmer N, Veyrat-Follet C, Frau F, Cohen C, Bozzi S, Cogswell M, Kumar D, Coulouvrat C, Leroy B, Fischer TZ, Sardi SP, Chandross KJ, Rubin LL, Wills AM, Kohane I, Lipnick SL.
BMC Neurol
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Illustrating potential effects of alternate control populations on real-world evidence-based statistical analyses.
Authors: Huang Y, Yuan W, Kohane IS, Beaulieu-Jones BK.
JAMIA Open
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Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians?
Authors: Beaulieu-Jones BK, Yuan W, Brat GA, Beam AL, Weber G, Ruffin M, Kohane IS.
NPJ Digit Med
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What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask.
Authors: Kohane IS, Aronow BJ, Avillach P, Beaulieu-Jones BK, Bellazzi R, Bradford RL, Brat GA, Cannataro M, Cimino JJ, García-Barrio N, Gehlenborg N, Ghassemi M, Gutiérrez-Sacristán A, Hanauer DA, Holmes JH, Hong C, Klann JG, Loh NHW, Luo Y, Mandl KD, Daniar M, Moore JH, Murphy SN, Neuraz A, Ngiam KY, Omenn GS, Palmer N, Patel LP, Pedrera-Jiménez M, Sliz P, South AM, Tan ALM, Taylor DM, Taylor BW, Torti C, Vallejos AK, Wagholikar KB, Weber GM, Cai T.
J Med Internet Res
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Temporal bias in case-control design: preventing reliable predictions of the future.
Authors: Yuan W, Beaulieu-Jones BK, Yu KH, Lipnick SL, Palmer N, Loscalzo J, Cai T, Kohane IS.
Nat Commun
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International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study.
Authors: Weber GM, Hong C, Palmer NP, Avillach P, Murphy SN, Gutiérrez-Sacristán A, Xia Z, Serret-Larmande A, Neuraz A, Omenn GS, Visweswaran S, Klann JG, South AM, Loh NHW, Cannataro M, Beaulieu-Jones BK, Bellazzi R, Agapito G, Alessiani M, Aronow BJ, Bell DS, Bellasi A, Benoit V, Beraghi M, Boeker M, Booth J, Bosari S, Bourgeois FT, Brown NW, Bucalo M, Chiovato L, Chiudinelli L, Dagliati A, Devkota B, DuVall SL, Follett RW, Ganslandt T, García Barrio N, Gradinger T, Griffier R, Hanauer DA, Holmes JH, Horki P, Huling KM, Issitt RW, Jouhet V, Keller MS, Kraska D, Liu M, Luo Y, Lynch KE, Malovini A, Mandl KD, Mao C, Maram A, Matheny ME, Maulhardt T, Mazzitelli M, Milano M, Moore JH, Morris JS, Morris M, Mowery DL, Naughton TP, Ngiam KY, Norman JB, Patel LP, Pedrera Jimenez M, Ramoni RB, Schriver ER, Scudeller L, Sebire NJ, Serrano Balazote P, Spiridou A, Tan AL, Tan BW, Tibollo V, Torti C, Trecarichi EM, Vitacca M, Zambelli A, Zucco C, Kohane IS, Cai T, Brat GA.
medRxiv
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Multinational Prevalence of Neurological Phenotypes in Patients Hospitalized with COVID-19.
Authors: Le TT, Gutiérrez-Sacristán A, Son J, Hong C, South AM, Beaulieu-Jones BK, Loh NHW, Luo Y, Morris M, Ngiam KY, Patel LP, Samayamuthu MJ, Schriver E, Tan AL, Moore J, Cai T, Omenn GS, Avillach P, Kohane IS, Visweswaran S, Mowery DL, Xia Z.
medRxiv
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Innovative methodological approaches for data integration to derive patterns across diverse, large-scale biomedical datasets.
Authors: Beaulieu-Jones B, Darabos C, Kim D, Verma A, Kobren SN.
Pac Symp Biocomput
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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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Regularization of Deep Neural Networks for EEG Seizure Detection to Mitigate Overfitting.
Authors: Saqib M, Zhu Y, Wang MD, Beaulieu-Jones B.
Proc COMPSAC
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