Pranav Rajpurkar

Pranav Rajpurkar, PhD

Assistant Professor of Biomedical Informatics

10 Shattuck Street, Boston, MA 02115

Pranav Rajpurkar is driven by a fundamental passion for building reliable artificial intelligence (AI) technologies for biomedical decision making. His lab approaches biomedical problems with a computational lens, developing AI algorithms, datasets, and interfaces that cut across computer vision, natural language processing, and structured health data. He has collaborated with clinicians across medical specialties, including radiology, cardiology, and pathology, to make some of the first demonstrations of expert-level deep learning algorithms and their effects on clinician decision making. Previously, Dr. Rajpurkar received his B.S., M.S., and Ph.D. degrees, all in Computer Science from Stanford University.

His lab’s current research directions include algorithm development for limited labeled data settings, high-quality dataset curation at scale, and the design of effective clinician-AI collaboration setups.

DBMI Research Areas

Courses

In the News

Predicting patient decompensation from continuous physiologic monitoring in the emergency department.
Authors: Sundrani S, Chen J, Jin BT, Abad ZSH, Rajpurkar P, Kim D.
NPJ Digit Med
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Foundation models for generalist medical artificial intelligence.
Authors: Moor M, Banerjee O, Abad ZSH, Krumholz HM, Leskovec J, Topol EJ, Rajpurkar P.
Nature
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A proof of concept for a deep learning system that can aid embryologists in predicting blastocyst survival after thaw.
Authors: Marsh P, Radif D, Rajpurkar P, Wang Z, Hariton E, Ribeiro S, Simbulan R, Kaing A, Lin W, Rajah A, Rabara F, Lungren M, Demirci U, Ng A, Rosen M.
Sci Rep
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Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning.
Authors: Tiu E, Talius E, Patel P, Langlotz CP, Ng AY, Rajpurkar P.
Nat Biomed Eng
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Self-supervised learning in medicine and healthcare.
Authors: Krishnan R, Rajpurkar P, Topol EJ.
Nat Biomed Eng
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Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography.
Authors: Jin BT, Palleti R, Shi S, Ng AY, Quinn JV, Rajpurkar P, Kim D.
J Am Med Inform Assoc
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Multimodal biomedical AI.
Authors: Acosta JN, Falcone GJ, Rajpurkar P, Topol EJ.
Nat Med
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The Need for Medical Artificial Intelligence That Incorporates Prior Images.
Authors: Acosta JN, Falcone GJ, Rajpurkar P.
Radiology
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Contrastive learning of heart and lung sounds for label-efficient diagnosis.
Authors: Soni PN, Shi S, Sriram PR, Ng AY, Rajpurkar P.
Patterns (N Y)
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Targeted plasma metabolomics combined with machine learning for the diagnosis of severe acute respiratory syndrome virus type 2.
Authors: Le AT, Wu M, Khan A, Phillips N, Rajpurkar P, Garland M, Magid K, Sibai M, Huang C, Sahoo MK, Bowen R, Cowan TM, Pinsky BA, Hogan CA.
Front Microbiol
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