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Pranav Rajpurkar
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2020 – today
- 2024
- [i56]Hong-Yu Zhou, Subathra Adithan, Julián Nicolás Acosta, Eric J. Topol, Pranav Rajpurkar:
A Generalist Learner for Multifaceted Medical Image Interpretation. CoRR abs/2405.07988 (2024) - [i55]Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar:
Learning Generalized Medical Image Representations through Image-Graph Contrastive Pretraining. CoRR abs/2405.09594 (2024) - [i54]Alyssa Huang, Oishi Banerjee, Kay Wu, Eduardo Pontes Reis, Pranav Rajpurkar:
FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores. CoRR abs/2405.20613 (2024) - [i53]Oishi Banerjee, Hong-Yu Zhou, Subathra Adithan, Stephen Kwak, Kay Wu, Pranav Rajpurkar:
Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation. CoRR abs/2406.06496 (2024) - [i52]Luyang Luo, Mingxiang Wu, Mei Li, Yi Xin, Qiong Wang, Varut Vardhanabhuti, Winnie CW Chu, Zhenhui Li, Juan Zhou, Pranav Rajpurkar, Hao Chen:
Towards Non-invasive and Personalized Management of Breast Cancer Patients from Multiparametric MRI via A Large Mixture-of-Modality-Experts Model. CoRR abs/2408.12606 (2024) - [i51]Xiaoman Zhang, Julián Nicolás Acosta, Hong-Yu Zhou, Pranav Rajpurkar:
Uncovering Knowledge Gaps in Radiology Report Generation Models through Knowledge Graphs. CoRR abs/2408.14397 (2024) - [i50]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, Rayyan A. Daghistani, Yuh-Min Chen, Heng-sheng Chao, Lars Heiliger, Moon Kim, Johannes Haubold, Frederic Jonske, Pranav Rajpurkar:
ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics. CoRR abs/2408.16208 (2024) - [i49]Vishwanatha M. Rao, Serena Zhang, Julián Nicolás Acosta, Subathra Adithan, Pranav Rajpurkar:
ReXErr: Synthesizing Clinically Meaningful Errors in Diagnostic Radiology Reports. CoRR abs/2409.10829 (2024) - [i48]Julián Nicolás Acosta, Xiaoman Zhang, Siddhant Dogra, Hong-Yu Zhou, Seyedmehdi Payabvash, Guido J. Falcone, Eric K. Oermann, Pranav Rajpurkar:
HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation. CoRR abs/2409.13038 (2024) - [i47]Luyang Luo, Jenanan Vairavamurthy, Xiaoman Zhang, Abhinav Kumar, Ramon R. Ter-Oganesyan, Stuart T. Schroff, Dan Shilo, Rydhwana Hossain, Mike Moritz, Pranav Rajpurkar:
ReXplain: Translating Radiology into Patient-Friendly Video Reports. CoRR abs/2410.00441 (2024) - [i46]Zifeng Wang, Hanyin Wang, Benjamin P. Danek, Ying Li, Christina Mack, Hoifung Poon, Yajuan Wang, Pranav Rajpurkar, Jimeng Sun:
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges. CoRR abs/2411.00024 (2024) - [i45]Serena Zhang, Sraavya Sambara, Oishi Banerjee, Julian Acosta, L. John Fahrner, Pranav Rajpurkar:
RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models. CoRR abs/2411.00299 (2024) - 2023
- [j15]Agustina Saenz, Zach Harned, Oishi Banerjee, Michael D. Abràmoff, Pranav Rajpurkar:
Autonomous AI systems in the face of liability, regulations and costs. npj Digit. Medicine 6 (2023) - [j14]Sameer Sundrani, Julie Chen, Boyang Tom Jin, Zahra Shakeri Hossein Abad, Pranav Rajpurkar, David A. Kim:
Predicting patient decompensation from continuous physiologic monitoring in the emergency department. npj Digit. Medicine 6 (2023) - [j13]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, Pranav Rajpurkar:
Evaluating progress in automatic chest X-ray radiology report generation. Patterns 4(9): 100802 (2023) - [c31]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, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. EMNLP 2023: 14414-14445 - [c30]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:
Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting. EMNLP (Findings) 2023: 14676-14688 - [c29]Alexander Ke, Shih-Cheng Huang, Chloe P. O'Connell, Michal Klimont, Serena Yeung, Pranav Rajpurkar:
Video pretraining advances 3D deep learning on chest CT tasks. MIDL 2023: 758-774 - [c28]Jaehwan Jeong, Katherine Tian, Andrew Li, Sina Hartung, Subathra Adithan, Fardad Behzadi, Juan Calle, David Osayande, Michael Pohlen, Pranav Rajpurkar:
Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation. MIDL 2023: 978-990 - [c27]Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar:
Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining. ML4H@NeurIPS 2023: 232-243 - [c26]Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, Pranav Rajpurkar:
Med-Flamingo: a Multimodal Medical Few-shot Learner. ML4H@NeurIPS 2023: 353-367 - [c25]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, Pranav Rajpurkar:
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. ML4H@NeurIPS 2023: 528-558 - [c24]Sameer Tajdin Khanna, Adam Dejl, Kibo Yoon, Steven QH Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar:
RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. MLHC 2023: 381-402 - [c23]Emma Chen, Aman Kansal, Julie Chen, Boyang Tom Jin, Julia Rachel Reisler, David A. Kim, Pranav Rajpurkar:
Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine. NeurIPS 2023 - [i44]Jaehwan Jeong, Katherine Tian, Andrew Li, Sina Hartung, Fardad Behzadi, Juan Calle, David Osayande, Michael Pohlen, Subathra Adithan, Pranav Rajpurkar:
Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation. CoRR abs/2303.17579 (2023) - [i43]Alexander Ke, Shih-Cheng Huang, Chloe P. O'Connell, Michal Klimont, Serena Yeung, Pranav Rajpurkar:
Video Pretraining Advances 3D Deep Learning on Chest CT Tasks. CoRR abs/2304.00546 (2023) - [i42]Kathryn Wantlin, Chenwei Wu, 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, Geoffrey H. Tison, Alex Tamkin, Pranav Rajpurkar:
BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors. CoRR abs/2304.08486 (2023) - [i41]Aakash Mishra, Rajat Mittal, Christy Jestin, Kostas Tingos, Pranav Rajpurkar:
Improving Zero-Shot Detection of Low Prevalence Chest Pathologies using Domain Pre-trained Language Models. CoRR abs/2306.08000 (2023) - [i40]Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Cyril Zakka, Yash Dalmia, Eduardo Pontes Reis, Pranav Rajpurkar, Jure Leskovec:
Med-Flamingo: a Multimodal Medical Few-shot Learner. CoRR abs/2307.15189 (2023) - [i39]Sameer Tajdin Khanna, Adam Dejl, Kibo Yoon, Quoc Hung Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar:
RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. CoRR abs/2308.05046 (2023) - [i38]Luke W. Sagers, James A. Diao, Luke Melas-Kyriazi, Matthew Groh, Pranav Rajpurkar, Adewole S. Adamson, Veronica Rotemberg, Roxana Daneshjou, Arjun K. Manrai:
Augmenting medical image classifiers with synthetic data from latent diffusion models. CoRR abs/2308.12453 (2023) - [i37]Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle:
Exploring the Boundaries of GPT-4 in Radiology. CoRR abs/2310.14573 (2023) - [i36]Benjamin Yan, Ruochen Liu, David E. Kuo, Subathra Adithan, Eduardo Pontes Reis, Stephen Kwak, Vasantha Kumar Venugopal, Chloe P. O'Connell, Agustina Saenz, Pranav Rajpurkar, Michael Moor:
Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting. CoRR abs/2310.17811 (2023) - [i35]Emma Chen, Aman Kansal, Julie Chen, Boyang Tom Jin, Julia Rachel Reisler, David A. Kim, Pranav Rajpurkar:
Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine. CoRR abs/2311.04937 (2023) - [i34]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, Pranav Rajpurkar:
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. CoRR abs/2311.09574 (2023) - 2022
- [j12]Boyang Tom Jin, Raj Palleti, Siyu Shi, Andrew Y. Ng, James V. Quinn, Pranav Rajpurkar, David A. Kim:
Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography. J. Am. Medical Informatics Assoc. 29(11): 1908-1918 (2022) - [j11]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:
Benchmarking saliency methods for chest X-ray interpretation. Nat. Mac. Intell. 4(10): 867-878 (2022) - [j10]Pratham N. Soni, Siyu Shi, Pranav R. Sriram, Andrew Y. Ng, Pranav Rajpurkar:
Contrastive learning of heart and lung sounds for label-efficient diagnosis. Patterns 3(1): 100400 (2022) - [c22]Damir Vrabac, Akshay Smit, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar:
MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning. MIDL 2022: 1301-1310 - [c21]Vignav Ramesh, Nathan Andrew Chi, Pranav Rajpurkar:
Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priors. ML4H@NeurIPS 2022: 456-473 - [i33]Jon Braatz, Pranav Rajpurkar, Stephanie Zhang, Andrew Y. Ng, Jeanne Shen:
Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia. CoRR abs/2201.01449 (2022) - [i32]Vignav Ramesh, Nathan Andrew Chi, Pranav Rajpurkar:
Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priors. CoRR abs/2210.06340 (2022) - [i31]Luke W. Sagers, James A. Diao, Matthew Groh, Pranav Rajpurkar, Adewole S. Adamson, Arjun K. Manrai:
Improving dermatology classifiers across populations using images generated by large diffusion models. CoRR abs/2211.13352 (2022) - 2021
- [b1]Pranav Rajpurkar:
Deep learning for medical image interpretation. Stanford University, USA, 2021 - [j9]Michael Ko, Emma Chen, Ashwin Agrawal, Pranav Rajpurkar, Anand Avati, Andrew Yan-Tak Ng, Sanjay Basu, Nigam H. Shah:
Improving hospital readmission prediction using individualized utility analysis. J. Biomed. Informatics 119: 103826 (2021) - [j8]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, Ilana Golub, Matthew J. Budoff, Felipe Kitamura, Marcelo Straus Takahashi, Ross W. Filice, Rajesh Shah, John Mongan, Kimberly Kallianos, Curtis P. Langlotz, Matthew P. Lungren, Andrew Y. Ng, Bhavik N. Patel:
Automated coronary calcium scoring using deep learning with multicenter external validation. npj Digit. Medicine 4 (2021) - [c20]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:
VisualCheXbert: addressing the discrepancy between radiology report labels and image labels. CHIL 2021: 105-115 - [c19]Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar:
CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation. CHIL 2021: 116-124 - [c18]Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren:
CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings. CHIL 2021: 125-132 - [c17]Viswesh Krishna, Anirudh Joshi, Damir Vrabac, Philip L. Bulterys, Eric Yang, Sebastian Fernandez-Pol, Andrew Y. Ng, Pranav Rajpurkar:
GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment. MICCAI (8) 2021: 519-528 - [c16]Soham Uday Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar:
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. MIDL 2021: 190-204 - [c15]Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar:
Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. MIDL 2021: 699-712 - [c14]Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar:
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. MIDL 2021: 728-744 - [c13]Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar:
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. ML4H@NeurIPS 2021: 156-167 - [c12]Mark Endo, Rayan Krishnan, Viswesh Krishna, Andrew Y. Ng, Pranav Rajpurkar:
Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model. ML4H@NeurIPS 2021: 209-219 - [c11]Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar:
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. MLHC 2021: 103-125 - [c10]Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar:
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. MLHC 2021: 755-769 - [c9]Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre J. Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar:
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. NeurIPS Datasets and Benchmarks 2021 - [c8]Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Y. Ng, Pranav Rajpurkar:
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. NeurIPS Datasets and Benchmarks 2021 - [i30]Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar:
CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation. CoRR abs/2101.06871 (2021) - [i29]Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren:
CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings. CoRR abs/2102.08660 (2021) - [i28]Soham Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar:
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. CoRR abs/2102.10484 (2021) - [i27]Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar:
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. CoRR abs/2102.10663 (2021) - [i26]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:
VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labels. CoRR abs/2102.11467 (2021) - [i25]Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar:
CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. CoRR abs/2103.04590 (2021) - [i24]Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar:
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. CoRR abs/2103.09957 (2021) - [i23]Akshay Smit, Damir Vrabac, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar:
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning. CoRR abs/2103.14339 (2021) - [i22]Saahil Jain, Akshay Smit, Andrew Y. Ng, Pranav Rajpurkar:
Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation. CoRR abs/2104.00793 (2021) - [i21]Christian Garbin, Pranav Rajpurkar, Jeremy Irvin, Matthew P. Lungren, Oge Marques:
Structured dataset documentation: a datasheet for CheXpert. CoRR abs/2105.03020 (2021) - [i20]Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar:
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. CoRR abs/2106.04452 (2021) - [i19]Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre J. Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar:
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. CoRR abs/2106.14463 (2021) - [i18]Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Y. Ng, Pranav Rajpurkar:
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. CoRR abs/2108.01764 (2021) - 2020
- [j7]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, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren:
PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. npj Digit. Medicine 3 (2020) - [j6]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, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren:
Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. npj Digit. Medicine 3 (2020) - [j5]Amirhossein Kiani, Bora Uyumazturk, Pranav Rajpurkar, Alex Wang, Rebecca Gao, Erik Jones, Yifan Yu, Curtis P. Langlotz, Robyn L. Ball, Thomas J. Montine, Brock A. Martin, Gerald J. Berry, Michael G. Ozawa, Florette K. Hazard, Ryanne A. Brown, Simon B. Chen, Mona Wood, Libby S. Allard, Lourdes Ylagan, Andrew Y. Ng, Jeanne Shen:
Impact of a deep learning assistant on the histopathologic classification of liver cancer. npj Digit. Medicine 3 (2020) - [j4]Pranav Rajpurkar, Chloe P. 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, Tom H. Boyles, Matthew P. Lungren:
CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV. npj Digit. Medicine 3 (2020) - [c7]Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren:
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. EMNLP (1) 2020: 1500-1519 - [c6]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, Matthew P. Lungren:
CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. ML4H@NeurIPS 2020: 318-327 - [i17]Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Phil Chen, Amirhossein Kiani, Jeremy Irvin, Andrew Y. Ng, Matthew P. Lungren:
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting. CoRR abs/2002.11379 (2020) - [i16]Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren:
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. CoRR abs/2004.09167 (2020) - [i15]Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Andrew Y. Ng, Matthew P. Lungren:
CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. CoRR abs/2007.06199 (2020) - [i14]Damir Vrabac, Akshay Smit, Rebecca Rojansky, Yasodha Natkunam, Ranjana H. Advani, Andrew Y. Ng, Sebastian Fernandez-Pol, Pranav Rajpurkar:
DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set. CoRR abs/2009.08123 (2020) - [i13]Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar:
MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. CoRR abs/2010.05352 (2020) - [i12]Viswesh Krishna, Anirudh Joshi, Philip L. Bulterys, Eric Yang, Andrew Y. Ng, Pranav Rajpurkar:
GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video. CoRR abs/2010.15269 (2020) - [i11]Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Jeremy Irvin, Andrew Y. Ng, Matthew P. Lungren:
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays. CoRR abs/2011.06129 (2020)
2010 – 2019
- 2019
- [j3]Maya Varma, Mandy Lu, Rachel Gardner, Jared Dunnmon, Nishith Khandwala, Pranav Rajpurkar, Jin Long, Christopher Beaulieu, Katie S. Shpanskaya, Li Fei-Fei, Matthew P. Lungren, Bhavik N. Patel:
Automated abnormality detection in lower extremity radiographs using deep learning. Nat. Mach. Intell. 1(12): 578-583 (2019) - [j2]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, Joseph Mammarappallil, A. J. Mariano, Geoffrey Riley, Jayne Seekins, Luyao Shen, Evan Zucker, Matthew P. Lungren:
Human-machine partnership with artificial intelligence for chest radiograph diagnosis. npj Digit. Medicine 2 (2019) - [j1]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, Joseph Mammarappallil, A. J. Mariano, Geoffrey Riley, Jayne Seekins, Luyao Shen, Evan Zucker, Matthew P. Lungren:
Author Correction: Human-machine partnership with artificial intelligence for chest radiograph diagnosis. npj Digit. Medicine 2 (2019) - [c5]Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng:
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. AAAI 2019: 590-597 - [i10]Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng:
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. CoRR abs/1901.07031 (2019) - 2018
- [c4]Pranav Rajpurkar, Robin Jia, Percy Liang:
Know What You Don't Know: Unanswerable Questions for SQuAD. ACL (2) 2018: 784-789 - [i9]Pranav Rajpurkar, Robin Jia, Percy Liang:
Know What You Don't Know: Unanswerable Questions for SQuAD. CoRR abs/1806.03822 (2018) - 2017
- [i8]Pranav Rajpurkar, Awni Y. Hannun, Masoumeh Haghpanahi, Codie Bourn, Andrew Y. Ng:
Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks. CoRR abs/1707.01836 (2017) - [i7]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:
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. CoRR abs/1711.05225 (2017) - [i6]Pranav Rajpurkar, Vinaya Polamreddi, Anusha Balakrishnan:
Malaria Likelihood Prediction By Effectively Surveying Households Using Deep Reinforcement Learning. CoRR abs/1711.09223 (2017) - [i5]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, Matthew P. Lungren, Andrew Y. Ng:
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. CoRR abs/1712.06957 (2017) - 2016
- [c3]Ethan Fast, William McGrath, Pranav Rajpurkar, Michael S. Bernstein:
Augur: Mining Human Behaviors from Fiction to Power Interactive Systems. CHI 2016: 237-247 - [c2]Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, Percy Liang:
SQuAD: 100, 000+ Questions for Machine Comprehension of Text. EMNLP 2016: 2383-2392 - [i4]Ethan Fast, William McGrath, Pranav Rajpurkar, Michael S. Bernstein:
Augur: Mining Human Behaviors from Fiction to Power Interactive Systems. CoRR abs/1602.06977 (2016) - [i3]Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, Percy Liang:
SQuAD: 100, 000+ Questions for Machine Comprehension of Text. CoRR abs/1606.05250 (2016) - 2015
- [c1]Ethan Fast, Pranav Rajpurkar, Michael S. Bernstein:
Text Mining Emergent Human Behaviors for Interactive Systems. CHI Extended Abstracts 2015: 2265-2270 - [i2]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, Andrew Y. Ng:
An Empirical Evaluation of Deep Learning on Highway Driving. CoRR abs/1504.01716 (2015) - [i1]Pranav Rajpurkar, Toki Migimatsu, Jeff Kiske, Royce Cheng-Yue, Sameep Tandon, Tao Wang, Andrew Y. Ng:
Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving. CoRR abs/1512.01872 (2015)
Coauthor Index
aka: Andrew Yan-Tak Ng
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