Tianx Cai

Tianxi Cai, ScD

Professor of Biomedical Informatics, Harvard Medical School
John Rock Professor of Population and Translational Data Sciences, Harvard T.H. Chan School of Public Health
Director, Translational Data Science Center for a Learning Health System (CELEHS)

10 Shattuck Street, Room 434, Boston, MA 02115

Tianxi Cai is a major player in developing analytical tools for mining EHR data and predictive modeling with biomedical data. She provides statistical leadership on several large-scale projects, including the NIH-funded Undiagnosed Diseases Network at DBMI. Cai's research lab develops novel statistical and machine learning methods for several areas including clinical trials, real world evidence, and personalized medicine using genomic and phenomic data. Cai received her ScD in Biostatistics at Harvard and was an assistant professor at the University of Washington before returning to Harvard as a faculty member in 2002.


DBMI Research Areas
Family history as the strongest predictor of aortic and peripheral aneurysms in patients with intracranial aneurysms.
Authors: Lai PMR, Akama-Garren E, Can A, Tirado SR, Castro VM, Dligach D, Finan S, Gainer VS, Shadick NA, Savova G, Murphy SN, Cai T, Weiss ST, Du R.
J Clin Neurosci
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Semi-supervised Double Deep Learning Temporal Risk Prediction (SeDDLeR) with Electronic Health Records.
Authors: Nogues IE, Wen J, Zhao Y, Bonzel CL, Castro VM, Lin Y, Xu S, Hou J, Cai T.
J Biomed Inform
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Semisupervised transfer learning for evaluation of model classification performance.
Authors: Wang L, Wang X, Liao KP, Cai T.
Biometrics
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LATTE: Label-efficient incident phenotyping from longitudinal electronic health records.
Authors: Wen J, Hou J, Bonzel CL, Zhao Y, Castro VM, Gainer VS, Weisenfeld D, Cai T, Ho YL, Panickan VA, Costa L, Hong C, Gaziano JM, Liao KP, Lu J, Cho K, Cai T.
Patterns (N Y)
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Endovascular Aneurysm Repair Devices as a Use Case for Postmarketing Surveillance of Medical Devices.
Authors: Wang X, Ayakulangara Panickan V, Cai T, Xiong X, Cho K, Cai T, Bourgeois FT.
JAMA Intern Med
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Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium.
Authors: Sperotto F, Gutiérrez-Sacristán A, Makwana S, Li X, Rofeberg VN, Cai T, Bourgeois FT, Omenn GS, Hanauer DA, Sáez C, Bonzel CL, Bucholz E, Dionne A, Elias MD, García-Barrio N, González TG, Issitt RW, Kernan KF, Laird-Gion J, Maidlow SE, Mandl KD, Ahooyi TM, Moraleda C, Morris M, Moshal KL, Pedrera-Jiménez M, Shah MA, South AM, Spiridou A, Taylor DM, Verdy G, Visweswaran S, Wang X, Xia Z, Zachariasse JM, Newburger JW, Avillach P.
EClinicalMedicine
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Semi-supervised calibration of noisy event risk (SCANER) with electronic health records.
Authors: Hong C, Liang L, Yuan Q, Cho K, Liao KP, Pencina MJ, Christiani DC, Cai T.
J Biomed Inform
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Utilizing biologic disease-modifying anti-rheumatic treatment sequences to subphenotype rheumatoid arthritis.
Authors: Das P, Weisenfeld D, Dahal K, De D, Feathers V, Coblyn JS, Weinblatt ME, Shadick NA, Cai T, Liao KP.
Arthritis Res Ther
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Identifying shared genetic architecture between rheumatoid arthritis and other conditions: a phenome-wide association study with genetic risk scores.
Authors: Zhang HG, McDermott G, Seyok T, Huang S, Dahal K, L'Yi S, Lea-Bonzel C, Stratton J, Weisenfeld D, Monach P, Raychaudhuri S, Yu KH, Cai T, Cui J, Hong C, Cai T, Liao KP.
EBioMedicine
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Potential pitfalls in the use of real-world data for studying long COVID.
Authors: Zhang HG, Honerlaw JP, Maripuri M, Samayamuthu MJ, Beaulieu-Jones BR, Baig HS, L'Yi S, Ho YL, Morris M, Panickan VA, Wang X, Weber GM, Liao KP, Visweswaran S, Tan BWQ, Yuan W, Gehlenborg N, Muralidhar S, Ramoni RB, Kohane IS, Xia Z, Cho K, Cai T, Brat GA.
Nat Med
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