Susanne Churchill

Susanne Churchill, PhD

Executive Director, DBMI, Harvard Medical School
Instructor in Medicine, Brigham and Women's Hospital

10 Shattuck St Boston MA 02115

Susanne Churchill received her PhD from Boston University School of Medicine and did her postdoctoral training at Harvard Medical School in the field of cardiovascular and renal physiology, progressing to instructor and lecturer. She co-founded the Institute for Circadian Physiology in Boston, where she served as chief operating officer while continuing her research in space medicine and teaching. She returned full time to HMS to serve as director of sponsored programs administration and subsequently was appointed associate dean for research. Churchill next joined forces with Isaac Kohane to lead the successful Informatics for Integrating Biology and the Bedside (i2b2) National Center for Biomedical Computing at Partners HealthCare as its executive director and principle investigator of the educational core. She joined DBMI in 2015 as executive director of the department, executive director of the Big Data to Knowledge (BD2K) Center of Excellence, executive director of the N-GRID (neuropsychiatric genome-scale and RDoC-Individualized domains) Center of Excellence in Genome Science and program director for the long-running Summer Institute in Biomedical Informatics (SIBMI). Churchill is also an instructor in the Channing Division of Network Medicine at Brigham and Women’s Hospital.

Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders.
Authors: Chen S, Tan ALM, Saad Menezes MC, Mao JF, Perry CL, Vella ME, Viswanadham VV, Kobren S, Churchill S, Kohane IS.
NPJ Precis Oncol
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The digital-physical divide for pathology research.
Authors: Kohane IS, Churchill S, Tan ALM, Vella M, Perry CL.
Lancet Digit Health
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An efficient landmark model for prediction of suicide attempts in multiple clinical settings.
Authors: Sheu YH, Sun J, Lee H, Castro VM, Barak-Corren Y, Song E, Madsen EM, Gordon WJ, Kohane IS, Churchill SE, Reis BY, Cai T, Smoller JW.
Psychiatry Res
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ATLAS: an automated association test using probabilistically linked health records with application to genetic studies.
Authors: Zhang HG, Hejblum BP, Weber GM, Palmer NP, Churchill SE, Szolovits P, Murphy SN, Liao KP, Kohane IS, Cai T.
J Am Med Inform Assoc
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Use of Narrative Concepts in Electronic Health Records to Validate Associations Between Genetic Factors and Response to Treatment of Inflammatory Bowel Diseases.
Authors: Ananthakrishnan AN, Cagan A, Cai T, Gainer VS, Savova G, Shaw SY, Churchill S, Burke KE, Karlson EW, Murphy SN, Kohane I, Liao KP, Xavier RJ.
Clin Gastroenterol Hepatol
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High-throughput phenotyping with electronic medical record data using a common semi-supervised approach (PheCAP).
Authors: Zhang Y, Cai T, Yu S, Cho K, Hong C, Sun J, Huang J, Ho YL, Ananthakrishnan AN, Xia Z, Shaw SY, Gainer V, Castro V, Link N, Honerlaw J, Huang S, Gagnon D, Karlson EW, Plenge RM, Szolovits P, Savova G, Churchill S, O'Donnell C, Murphy SN, Gaziano JM, Kohane I, Cai T, Liao KP.
Nat Protoc
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The Impact of Autonomy-Framed and Control-Framed Implementation Intentions on Snacking Behaviour: The Moderating Effect of Eating Self-Efficacy.
Authors: Churchill S, Pavey L, Sparks P.
Appl Psychol Health Well Being
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Probabilistic record linkage of de-identified research datasets with discrepancies using diagnosis codes.
Authors: Hejblum BP, Weber GM, Liao KP, Palmer NP, Churchill S, Shadick NA, Szolovits P, Murphy SN, Kohane IS, Cai T.
Sci Data
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Enabling phenotypic big data with PheNorm.
Authors: Yu S, Ma Y, Gronsbell J, Cai T, Ananthakrishnan AN, Gainer VS, Churchill SE, Szolovits P, Murphy SN, Kohane IS, Liao KP, Cai T.
J Am Med Inform Assoc
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Surrogate-assisted feature extraction for high-throughput phenotyping.
Authors: Yu S, Chakrabortty A, Liao KP, Cai T, Ananthakrishnan AN, Gainer VS, Churchill SE, Szolovits P, Murphy SN, Kohane IS, Cai T.
J Am Med Inform Assoc
View full abstract on Pubmed