Text Mining Emergent Human Behaviors for Interactive Systems. - Ethan Fast; Pranav Rajpurkar; Michael S. Bernstein (CHI Extended Abstracts, 2015)

An Empirical Evaluation of Deep Learning on Highway Driving. - Brody Huval; Tao Wang; Sameep Tandon; Jeff Kiske; Will Song; Joel Pazhayampallil; Mykhaylo Andriluka; Pranav Rajpurkar; Toki Migimatsu; Royce Cheng-Yue; Fernando A. Mujica; Adam Coates 002; et al. (CoRR, 2015)

Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving. - Pranav Rajpurkar; Toki Migimatsu; Jeff Kiske; Royce Cheng-Yue; Sameep Tandon; Tao Wang; Andrew Y. Ng (CoRR, 2015)

Augur: Mining Human Behaviors from Fiction to Power Interactive Systems. - Ethan Fast; William McGrath; Pranav Rajpurkar; Michael S. Bernstein (CHI, 2016)

SQuAD: 100, 000+ Questions for Machine Comprehension of Text. - Pranav Rajpurkar; Jian Zhang 049; Konstantin Lopyrev; Percy Liang (EMNLP, 2016)

Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks. - Pranav Rajpurkar; Awni Y. Hannun; Masoumeh Haghpanahi; Codie Bourn; Andrew Y. Ng (CoRR, 2017)

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. - Pranav Rajpurkar; Jeremy Irvin; Kaylie Zhu; Brandon Yang; Hershel Mehta; Tony Duan; Daisy Yi Ding; Aarti Bagul; Curtis P. Langlotz; Katie S. Shpanskaya; Matthew P. Lungren; Andrew Y. Ng (CoRR, 2017)

Malaria Likelihood Prediction By Effectively Surveying Households Using Deep Reinforcement Learning. - Pranav Rajpurkar; Vinaya Polamreddi; Anusha Balakrishnan (CoRR, 2017)

MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. - Pranav Rajpurkar; Jeremy Irvin; Aarti Bagul; Daisy Yi Ding; Tony Duan; Hershel Mehta; Brandon Yang; Kaylie Zhu; Dillon Laird; Robyn L. Ball; Curtis P. Langlotz; Katie S. Shpanskaya; et al. (CoRR, 2017)

Know What You Don't Know: Unanswerable Questions for SQuAD. - Pranav Rajpurkar; Robin Jia; Percy Liang (ACL (2), 2018)

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. - Jeremy Irvin; Pranav Rajpurkar; Michael Ko; Yifan Yu 005; Silviana Ciurea-Ilcus; Christopher Chute; Henrik Marklund; Behzad Haghgoo; Robyn L. Ball; Katie S. Shpanskaya; Jayne Seekins; David A. Mong; et al. (AAAI, 2019)

Automated abnormality detection in lower extremity radiographs using deep learning. - Maya Varma; Mandy Lu; Rachel Gardner; Jared Dunnmon; Nishith Khandwala; Pranav Rajpurkar; Jin Long; Christopher Beaulieu; Katie S. Shpanskaya; Li Fei-Fei 001; Matthew P. Lungren; Bhavik N. Patel (Nat. Mach. Intell., 2019)

Human-machine partnership with artificial intelligence for chest radiograph diagnosis. - Bhavik N. Patel; Louis B. Rosenberg; Gregg Willcox; David Baltaxe; Mimi Lyons; Jeremy Irvin; Pranav Rajpurkar; Timothy Amrhein; Rajan Gupta; Safwan Halabi; Curtis P. Langlotz; Edward Lo; et al. (npj Digit. Medicine, 2019)

Author Correction: Human-machine partnership with artificial intelligence for chest radiograph diagnosis. - Bhavik N. Patel; Louis B. Rosenberg; Gregg Willcox; David Baltaxe; Mimi Lyons; Jeremy Irvin; Pranav Rajpurkar; Timothy Amrhein; Rajan Gupta; Safwan Halabi; Curtis P. Langlotz; Edward Lo; et al. (npj Digit. Medicine, 2019)

Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. - Akshay Smit; Saahil Jain; Pranav Rajpurkar; Anuj Pareek; Andrew Y. Ng; Matthew P. Lungren (EMNLP (1), 2020)

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. - Nick A. Phillips; Pranav Rajpurkar; Mark Sabini; Rayan Krishnan; Sharon Zhou; Anuj Pareek; Nguyet Minh Phu; Chris Wang; Mudit Jain; Du Nguyen Duong; Steven Q. H. Truong; Andrew Y. Ng; et al. (ML4H@NeurIPS, 2020)

CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting. - Pranav Rajpurkar; Anirudh Joshi; Anuj Pareek; Phil Chen; Amirhossein Kiani; Jeremy Irvin; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. - Akshay Smit; Saahil Jain; Pranav Rajpurkar; Anuj Pareek; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. - Nick A. Phillips; Pranav Rajpurkar; Mark Sabini; Rayan Krishnan; Sharon Zhou; Anuj Pareek; Nguyet Minh Phu; Chris Wang; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set. - Damir Vrabac; Akshay Smit; Rebecca Rojansky; Yasodha Natkunam; Ranjana H. Advani; Andrew Y. Ng; Sebastian Fernandez-Pol; Pranav Rajpurkar (CoRR, 2020)

GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video. - Viswesh Krishna; Anirudh Joshi; Philip L. Bulterys; Eric Yang; Andrew Y. Ng; Pranav Rajpurkar (CoRR, 2020)

CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays. - Pranav Rajpurkar; Anirudh Joshi; Anuj Pareek; Jeremy Irvin; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. - Shih-Cheng Huang; Tanay Kothari; Imon Banerjee; Christopher Chute; Robyn L. Ball; Norah Borus; Andrew Huang; Bhavik N. Patel; Pranav Rajpurkar; Jeremy Irvin; Jared Dunnmon; Joseph Bledsoe; et al. (npj Digit. Medicine, 2020)

Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. - Shih-Cheng Huang; Tanay Kothari; Imon Banerjee; Christopher Chute; Robyn L. Ball; Norah Borus; Andrew Huang; Bhavik N. Patel; Pranav Rajpurkar; Jeremy Irvin; Jared Dunnmon; Joseph Bledsoe; et al. (npj Digit. Medicine, 2020)

Impact of a deep learning assistant on the histopathologic classification of liver cancer. - Amirhossein Kiani; Bora Uyumazturk; Pranav Rajpurkar; Alex Wang; Rebecca Gao; Erik Jones; Yifan Yu 005; Curtis P. Langlotz; Robyn L. Ball; Thomas J. Montine; Brock A. Martin; Gerald J. Berry; et al. (npj Digit. Medicine, 2020)

CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV. - Pranav Rajpurkar; Chloe O'Connell; Amit Schechter; Nishit Asnani; Jason Li; Amirhossein Kiani; Robyn L. Ball; Marc Mendelson; Gary Maartens; Daniël J. van Hoving; Rulan Griesel; Andrew Y. Ng; et al. (npj Digit. Medicine, 2020)

VisualCheXbert: addressing the discrepancy between radiology report labels and image labels. - Saahil Jain; Akshay Smit; Steven Q. H. Truong; Chanh D. T. Nguyen; Minh-Thanh Huynh; Mudit Jain; Victoria A. Young; Andrew Y. Ng; Matthew P. Lungren; Pranav Rajpurkar (CHIL, 2021)

CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation. - Alexander Ke; William Ellsworth; Oishi Banerjee; Andrew Y. Ng; Pranav Rajpurkar (CHIL, 2021)

CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings. - Pranav Rajpurkar; Anirudh Joshi; Anuj Pareek; Andrew Y. Ng; Matthew P. Lungren (CHIL, 2021)

GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment. - Viswesh Krishna; Anirudh Joshi; Damir Vrabac; Philip L. Bulterys; Eric Yang; Sebastian Fernandez-Pol; Andrew Y. Ng; Pranav Rajpurkar (MICCAI (8), 2021)

CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. - Soham Uday Gadgil; Mark Endo; Emily Wen; Andrew Y. Ng; Pranav Rajpurkar (MIDL, 2021)

Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. - Siyu Shi; Ishaan Malhi; Kevin Tran; Andrew Y. Ng; Pranav Rajpurkar (MIDL, 2021)

MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. - Hari Sowrirajan; Jingbo Yang; Andrew Y. Ng; Pranav Rajpurkar (MIDL, 2021)

Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model. - Mark Endo; Rayan Krishnan; Viswesh Krishna; Andrew Y. Ng; Pranav Rajpurkar (ML4H@NeurIPS, 2021)

3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. - Bryan Gopal; Ryan W. Han; Gautham Raghupathi; Andrew Y. Ng; Geoffrey H. Tison; Pranav Rajpurkar (ML4H@NeurIPS, 2021)

CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. - Emma Chen; Andy Kim; Rayan Krishnan; Jin Long; Andrew Y. Ng; Pranav Rajpurkar (MLHC, 2021)

MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. - Yen Nhi Truong Vu; Richard Wang; Niranjan Balachandar; Can Liu; Andrew Y. Ng; Pranav Rajpurkar (MLHC, 2021)

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. - Saahil Jain; Ashwin Agrawal; Adriel Saporta; Steven Q. H. Truong; Du Nguyen Duong; Tan Bui; Pierre J. Chambon; Yuhao Zhang 004; Matthew P. Lungren; Andrew Y. Ng; Curtis P. Langlotz; Pranav Rajpurkar (NeurIPS Datasets and Benchmarks, 2021)

Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. - Cécile Logé; Emily Ross; David Yaw Amoah Dadey; Saahil Jain; Adriel Saporta; Andrew Y. Ng; Pranav Rajpurkar (NeurIPS Datasets and Benchmarks, 2021)

CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. - Siyu Shi; Ishaan Malhi; Kevin Tran; Andrew Y. Ng; Pranav Rajpurkar (CoRR, 2021)

MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning. - Akshay Smit; Damir Vrabac; Yujie He; Andrew Y. Ng; Andrew L. Beam; Pranav Rajpurkar (CoRR, 2021)

Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation. - Saahil Jain; Akshay Smit; Andrew Y. Ng; Pranav Rajpurkar (CoRR, 2021)

Structured dataset documentation: a datasheet for CheXpert. - Christian Garbin; Pranav Rajpurkar; Jeremy Irvin; Matthew P. Lungren; Oge Marques (CoRR, 2021)

Improving hospital readmission prediction using individualized utility analysis. - Michael Ko; Emma Chen; Ashwin Agrawal; Pranav Rajpurkar; Anand Avati; Andrew Yan-Tak Ng; Sanjay Basu; Nigam H. Shah (J. Biomed. Informatics, 2021)

Automated coronary calcium scoring using deep learning with multicenter external validation. - David Eng; Christopher Chute; Nishith Khandwala; Pranav Rajpurkar; Jin Long; Sam Shleifer; Mohamed H. Khalaf; Alexander T. Sandhu; Fátima Rodriguez; David J. Maron; Saeed Seyyedi; Daniele Marin; et al. (npj Digit. Medicine, 2021)

Deep learning for medical image interpretation. - Pranav Rajpurkar (2021)

MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning. - Damir Vrabac; Akshay Smit; Yujie He; Andrew Y. Ng; Andrew L. Beam; Pranav Rajpurkar (MIDL, 2022)

Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priors. - Vignav Ramesh; Nathan Andrew Chi; Pranav Rajpurkar (ML4H@NeurIPS, 2022)

Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia. - Jon Braatz; Pranav Rajpurkar; Stephanie Zhang; Andrew Y. Ng; Jeanne Shen (CoRR, 2022)

Improving dermatology classifiers across populations using images generated by large diffusion models. - Luke W. Sagers; James A. Diao; Matthew Groh; Pranav Rajpurkar; Adewole S. Adamson; Arjun K. Manrai (CoRR, 2022)

Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography. - Boyang Tom Jin; Raj Palleti; Siyu Shi; Andrew Y. Ng; James V. Quinn; Pranav Rajpurkar; David A. Kim (J. Am. Medical Informatics Assoc., 2022)

Contrastive learning of heart and lung sounds for label-efficient diagnosis. - Pratham N. Soni; Siyu Shi; Pranav R. Sriram; Andrew Y. Ng; Pranav Rajpurkar (Patterns, 2022)

Benchmarking saliency methods for chest X-ray interpretation. - Adriel Saporta; Xiaotong Gui; Ashwin Agrawal; Anuj Pareek; Steven Q. H. Truong; Chanh D. T. Nguyen; Van Doan Ngo; Jayne Seekins; Francis G. Blankenberg; Andrew Y. Ng; Matthew P. Lungren; Pranav Rajpurkar (Nat. Mac. Intell., 2022)

Exploring the Boundaries of GPT-4 in Radiology. - Qianchu Liu; Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Maria Wetscherek; Robert Tinn; Harshita Sharma; Fernando Pérez-García; Anton Schwaighofer; Pranav Rajpurkar; Sameer Tajdin Khanna; et al. (EMNLP, 2023)

Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting. - Benjamin Yan; Ruochen Liu; David E. Kuo; Subathra Adithan; Eduardo Pontes Reis; Stephen Kwak; Vasantha Kumar Venugopal; Chloe O'Connell; Agustina Saenz; Pranav Rajpurkar; Michael Moor (EMNLP (Findings), 2023)

Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation. - Jaehwan Jeong; Katherine Tian; Andrew Li; Sina Hartung; Subathra Adithan; Fardad Behzadi; Juan Calle; David Osayande; Michael Pohlen; Pranav Rajpurkar (MIDL, 2023)

Video pretraining advances 3D deep learning on chest CT tasks. - Alexander Ke; Shih-Cheng Huang; Chloe O'Connell; Michal Klimont; Serena Yeung; Pranav Rajpurkar (MIDL, 2023)

Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining. - Sameer Tajdin Khanna; Daniel Michael; Marinka Zitnik; Pranav Rajpurkar (ML4H@NeurIPS, 2023)

Med-Flamingo: a Multimodal Medical Few-shot Learner. - Michael Moor; Qian Huang; Shirley Wu; Michihiro Yasunaga; Yash Dalmia; Jure Leskovec; Cyril Zakka; Eduardo Pontes Reis; Pranav Rajpurkar (ML4H@NeurIPS, 2023)

LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. - Vivek Shankar; Xiaoli Yang; Vrishab Krishna; Brent Tan; Oscar Silva; Rebecca Rojansky; Andrew Y. Ng; Fabiola Valvert; Edward Briercheck; David Weinstock; Yasodha Natkunam; Sebastian Fernandez-Pol; et al. (ML4H@NeurIPS, 2023)

RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. - Sameer Tajdin Khanna; Adam Dejl; Kibo Yoon; Steven Q. H. Truong; Hanh Duong; Agustina Saenz; Pranav Rajpurkar (MLHC, 2023)

Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine. - Emma Chen; Aman Kansal; Julie Chen; Boyang Tom Jin; Julia Rachel Reisler; David A. Kim; Pranav Rajpurkar (NeurIPS, 2023)

BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors. - Kathryn Wantlin; Chenwei Wu 006; Shih-Cheng Huang; Oishi Banerjee; Farah Dadabhoy; Veeral Vipin Mehta; Ryan Wonhee Han; Fang Cao; Raja R. Narayan; Errol Colak; Adewole S. Adamson; Laura Heacock; et al. (CoRR, 2023)

Improving Zero-Shot Detection of Low Prevalence Chest Pathologies using Domain Pre-trained Language Models. - Aakash Mishra; Rajat Mittal; Christy Jestin; Kostas Tingos; Pranav Rajpurkar (CoRR, 2023)

RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. - Sameer Tajdin Khanna; Adam Dejl; Kibo Yoon; Quoc Hung Truong; Hanh Duong; Agustina Saenz; Pranav Rajpurkar (CoRR, 2023)

Augmenting medical image classifiers with synthetic data from latent diffusion models. - Luke W. Sagers; James A. Diao; Luke Melas-Kyriazi; Matthew Groh; Pranav Rajpurkar; Adewole S. Adamson; Veronica Rotemberg; Roxana Daneshjou; Arjun K. Manrai (CoRR, 2023)

Autonomous AI systems in the face of liability, regulations and costs. - Agustina Saenz; Zach Harned; Oishi Banerjee; Michael D. Abràmoff; Pranav Rajpurkar (npj Digit. Medicine, 2023)

Predicting patient decompensation from continuous physiologic monitoring in the emergency department. - Sameer Sundrani; Julie Chen; Boyang Tom Jin; Zahra Shakeri Hossein Abad; Pranav Rajpurkar; David A. Kim (npj Digit. Medicine, 2023)

Evaluating progress in automatic chest X-ray radiology report generation. - Feiyang Yu; Mark Endo; Rayan Krishnan; Ian Pan; Andy Tsai; Eduardo Pontes Reis; Eduardo Kaiser Ururahy Nunes Fonseca; Henrique Min Ho Lee; Zahra Shakeri Hossein Abad; Andrew Y. Ng; Curtis P. Langlotz; Vasantha Kumar Venugopal; et al. (Patterns, 2023)

RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models. - Serena Zhang; Sraavya Sambara; Oishi Banerjee; Julián Nicolás Acosta; L. John Fahrner; Pranav Rajpurkar (ML4H@NeurIPS, 2024)

MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting. - Arnold Caleb Asiimwe; Didac Suris Coll-Vinent; Pranav Rajpurkar; Carl Vondrick (MLHC, 2024)

Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation. - Oishi Banerjee; Hong-Yu Zhou; Kay Wu; Subathra Adithan; Stephen Kwak; Pranav Rajpurkar (MLHC, 2024)

FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores. - Alyssa Huang; Oishi Banerjee; Kay Wu; Eduardo Pontes Reis; Pranav Rajpurkar (MLHC, 2024)

A Generalist Learner for Multifaceted Medical Image Interpretation. - Hong-Yu Zhou; Subathra Adithan; Julián Nicolás Acosta; Eric J. Topol; Pranav Rajpurkar (CoRR, 2024)

Towards Non-invasive and Personalized Management of Breast Cancer Patients from Multiparametric MRI via A Large Mixture-of-Modality-Experts Model. - Luyang Luo; Mingxiang Wu; Mei Li; Yi Xin; Qiong Wang 001; Varut Vardhanabhuti; Winnie C. W. Chu; Zhenhui Li; Juan Zhou; Pranav Rajpurkar; Hao Chen 011 (CoRR, 2024)

ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics. - Oishi Banerjee; Agustina Saenz; Kay Wu; Warren Clements; Adil Zia; Dominic Buensalido; Helen Kavnoudias; Alain S. Abi-Ghanem; Nour El Ghawi; Cibele Luna; Patricia Castillo; Khaled Al-Surimi; et al. (CoRR, 2024)

ReXErr: Synthesizing Clinically Meaningful Errors in Diagnostic Radiology Reports. - Vishwanatha M. Rao; Serena Zhang; Julián Nicolás Acosta; Subathra Adithan; Pranav Rajpurkar (CoRR, 2024)

ReXplain: Translating Radiology into Patient-Friendly Video Reports. - Luyang Luo; Jenanan Vairavamurthy; Xiaoman Zhang; Abhinav Kumar; Ramon R. Ter-Oganesyan; Stuart T. Schroff; Dan Shilo; Rydhwana Hossain; Mike Moritz; Pranav Rajpurkar (CoRR, 2024)

A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges. - Zifeng Wang 008; Hanyin Wang; Benjamin P. Danek; Ying Li; Christina Mack; Hoifung Poon; Yajuan Wang; Pranav Rajpurkar; Jimeng Sun 001 (CoRR, 2024)

ReXrank: A Public Leaderboard for AI-Powered Radiology Report Generation. - Xiaoman Zhang; Hong-Yu Zhou; Xiaoli Yang; Oishi Banerjee; Julián Nicolás Acosta; Josh Miller; Ouwen Huang; Pranav Rajpurkar (CoRR, 2024)

MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting. - Arnold Caleb Asiimwe; Dídac Surís; Pranav Rajpurkar; Carl Vondrick (CoRR, 2024)

The Impact of AI Assistance on Radiology Reporting: A Pilot Study Using Simulated AI Draft Reports. - Julián Nicolás Acosta; Siddhant Dogra; Subathra Adithan; Kay Wu; Michael Moritz; Stephen Kwak; Pranav Rajpurkar (CoRR, 2024)

a2z-1 for Multi-Disease Detection in Abdomen-Pelvis CT: External Validation and Performance Analysis Across 21 Conditions. - Pranav Rajpurkar; Julián Nicolás Acosta; Siddhant Dogra; Jaehwan Jeong; Deepanshu Jindal; Michael Moritz; Samir Rajpurkar (CoRR, 2024)

ReXTrust: A Model for Fine-Grained Hallucination Detection in AI-Generated Radiology Reports. - Romain Hardy; Sung Eun Kim; Pranav Rajpurkar (CoRR, 2024)

Reimbursement in the age of generalist radiology artificial intelligence. - Siddhant Dogra; Ezequiel; Pranav Rajpurkar (npj Digit. Medicine, 2024)

HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation. - Julián Nicolás Acosta; Xiaoman Zhang; Siddhant Dogra; Hong-Yu Zhou; Seyedmehdi Payabvash; Guido J. Falcone; Eric Karl Oermann; Pranav Rajpurkar (CHIL, 2025)

Uncovering Knowledge Gaps in Radiology Report Generation Models through Knowledge Graphs. - Xiaoman Zhang; Julián Nicolás Acosta; Hong-Yu Zhou; Pranav Rajpurkar (CHIL, 2025)

FactCheXcker: Mitigating Measurement Hallucinations in Chest X-ray Report Generation Models. - Alice Heiman; Xiaoman Zhang; Emma Chen; Sung Eun Kim; Pranav Rajpurkar (CVPR, 2025)

How generative AI voice agents will transform medicine. - Scott J. Adams; Julián Nicolás Acosta; Pranav Rajpurkar (npj Digit. Medicine, 2025)

Optimizing AI solutions for population health in primary care. - Sanjay Basu; Pablo Bermudez-Canete; Tannen Christopher Hall; Pranav Rajpurkar (npj Digit. Medicine, 2025)

Multimodal generative AI for interpreting 3D medical images and videos. - Jung-Oh Lee; Hong-Yu Zhou; Tyler M. Berzin; Daniel K. Sodickson; Pranav Rajpurkar (npj Digit. Medicine, 2025)

A perspective for adapting generalist AI to specialized medical AI applications and their challenges. - Zifeng Wang 008; Hanyin Wang; Benjamin P. Danek; Ying Li; Christina Mack; Luk Arbuckle; Devyani Biswal; Hoifung Poon; Yajuan Wang; Pranav Rajpurkar; Cao Xiao; Jimeng Sun 001 (npj Digit. Medicine, 2025)

A Data-Efficient Pan-Tumor Foundation Model for Oncology CT Interpretation. - Wenhui Lei; Hanyu Chen; Zitian Zhang; Luyang Luo; Qiong Xiao; Yannian Gu; Peng Gao; Yankai Jiang 003; Ci Wang; Guangtao Wu; Tongjia Xu; Yingjie Zhang; et al. (CoRR, 2025)

FreeTumor: Large-Scale Generative Tumor Synthesis in Computed Tomography Images for Improving Tumor Recognition. - Linshan Wu; Jiaxin Zhuang; Yanning Zhou 003; Sunan He; Jiabo Ma; Luyang Luo; Xi Wang 013; Xuefeng Ni; Xiaoling Zhong; Mingxiang Wu; Yinghua Zhao; Xiaohui Duan; et al. (CoRR, 2025)

ReXGradient-160K: A Large-Scale Publicly Available Dataset of Chest Radiographs with Free-text Reports. - Xiaoman Zhang; Julián Nicolás Acosta; Josh Miller; Ouwen Huang; Pranav Rajpurkar (CoRR, 2025)

ReXVQA: A Large-scale Visual Question Answering Benchmark for Generalist Chest X-ray Understanding. - Ankit Pal; Jung-Oh Lee; Xiaoman Zhang; Malaikannan Sankarasubbu; Seunghyeon Roh; Won Jung Kim; Meesun Lee; Pranav Rajpurkar (CoRR, 2025)

ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports. - Mohammed Baharoon; Luyang Luo; Michael Moritz; Abhinav Kumar; Sung Eun Kim; Xiaoman Zhang; Miao Zhu; Mahmoud Hussain Alabbad; Maha Sbayel Alhazmi; Neel P. Mistry; Kent Ryan Kleinschmidt; Brady Chrisler; et al. (CoRR, 2025)

Voice-guided Orchestrated Intelligence for Clinical Evaluation (VOICE): A Voice AI Agent System for Prehospital Stroke Assessment. - Julián Nicolás Acosta; Scott J. Adams; Julius Kernbach; Romain Hardy; Sung Eun Kim; Luyang Luo; Xiaoman Zhang; Shreya Johri; Mohammed Baharoon; Pranav Rajpurkar (CoRR, 2025)