Pranav Rajpurkar

Pranav Rajpurkar, PhD

Assistant Professor of Biomedical Informatics

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

Multimodal generative AI for interpreting 3D medical images and videos.
Authors: Lee JO, Zhou HY, Berzin TM, Sodickson DK, Rajpurkar P.
NPJ Digit Med
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A Dataset for Understanding Radiologist-Artificial Intelligence Collaboration.
Authors: Moehring A, Kutwal M, Huang R, Banerjee O, Jacobi A, Eber C, Mendoza D, Chung M, Dayan E, Gupta Y, Bui TDT, Truong SQH, Pareek A, Langlotz CP, Lungren MP, Agarwal N, Rajpurkar P, Salz T.
Sci Data
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A large model for non-invasive and personalized management of breast cancer from multiparametric MRI.
Authors: Luo L, Wu M, Li M, Xin Y, Wang Q, Vardhanabhuti V, Chu WC, Li Z, Zhou J, Rajpurkar P, Chen H.
Nat Commun
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Coordinated AI agents for advancing healthcare.
Authors: Moritz M, Topol E, Rajpurkar P.
Nat Biomed Eng
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Multimodal generative AI for medical image interpretation.
Authors: Rao VM, Hla M, Moor M, Adithan S, Kwak S, Topol EJ, Rajpurkar P.
Nature
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From data to artificial intelligence: evaluating the readiness of gastrointestinal endoscopy datasets.
Authors: Elamin S, Johri S, Rajpurkar P, Geisler E, Berzin TM.
J Can Assoc Gastroenterol
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A clinical certification pathway for generalist medical AI systems.
Authors: Rajpurkar P, Topol EJ.
Lancet
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ReXErr: Synthesizing Clinically Meaningful Errors in Diagnostic Radiology Reports.
Authors: Rao VM, Zhang S, Acosta JN, Adithan S, Rajpurkar P.
Pac Symp Biocomput
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ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics.
Authors: Banerjee O, Saenz A, Wu K, Clements W, Zia A, Buensalido D, Kavnoudias H, Abi-Ghanem AS, Ghawi NE, Luna C, Castillo P, Al-Surimi K, Daghistani RA, Chen YM, Chao HS, Heiliger L, Kim M, Haubold J, Jonske F, Rajpurkar P.
Pac Symp Biocomput
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An evaluation framework for clinical use of large language models in patient interaction tasks.
Authors: Johri S, Jeong J, Tran BA, Schlessinger DI, Wongvibulsin S, Barnes LA, Zhou HY, Cai ZR, Van Allen EM, Kim D, Daneshjou R, Rajpurkar P.
Nat Med
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