Pranav Rajpurkar

Orcid: 0000-0002-8030-3727

According to our database1, Pranav Rajpurkar authored at least 69 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Evaluating progress in automatic chest X-ray radiology report generation.
Patterns, September, 2023

Predicting patient decompensation from continuous physiologic monitoring in the emergency department.
npj Digit. Medicine, 2023

Autonomous AI systems in the face of liability, regulations and costs.
npj Digit. Medicine, 2023

Augmenting medical image classifiers with synthetic data from latent diffusion models.
CoRR, 2023

RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction.
CoRR, 2023

Improving Zero-Shot Detection of Low Prevalence Chest Pathologies using Domain Pre-trained Language Models.
CoRR, 2023

BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors.
CoRR, 2023

Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction.
Proceedings of the Machine Learning for Healthcare Conference, 2023

LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype.
Proceedings of the Machine Learning for Health, 2023

Med-Flamingo: a Multimodal Medical Few-shot Learner.
Proceedings of the Machine Learning for Health, 2023

Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining.
Proceedings of the Machine Learning for Health, 2023

Video pretraining advances 3D deep learning on chest CT tasks.
Proceedings of the Medical Imaging with Deep Learning, 2023

Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation.
Proceedings of the Medical Imaging with Deep Learning, 2023

Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023


2022
Benchmarking saliency methods for chest X-ray interpretation.
Nat. Mac. Intell., October, 2022

Contrastive learning of heart and lung sounds for label-efficient diagnosis.
Patterns, 2022

Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography.
J. Am. Medical Informatics Assoc., 2022

Improving dermatology classifiers across populations using images generated by large diffusion models.
CoRR, 2022

Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia.
CoRR, 2022

Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priors.
Proceedings of the Machine Learning for Health, 2022

MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021
Deep learning for medical image interpretation.
PhD thesis, 2021

Automated coronary calcium scoring using deep learning with multicenter external validation.
npj Digit. Medicine, 2021

Improving hospital readmission prediction using individualized utility analysis.
J. Biomed. Informatics, 2021

Structured dataset documentation: a datasheet for CheXpert.
CoRR, 2021

Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation.
CoRR, 2021

MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning.
CoRR, 2021

CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays.
CoRR, 2021

Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation.
Proceedings of the Machine Learning for Healthcare Conference, 2021

CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays.
Proceedings of the Machine Learning for Healthcare Conference, 2021

3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations.
Proceedings of the Machine Learning for Health, 2021

Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model.
Proceedings of the Machine Learning for Health, 2021

MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation.
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

VisualCheXbert: addressing the discrepancy between radiology report labels and image labels.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020
CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV.
npj Digit. Medicine, 2020

Impact of a deep learning assistant on the histopathologic classification of liver cancer.
npj Digit. Medicine, 2020

Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.
npj Digit. Medicine, 2020

PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.
npj Digit. Medicine, 2020

CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays.
CoRR, 2020

GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video.
CoRR, 2020

DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set.
CoRR, 2020

CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness.
CoRR, 2020

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT.
CoRR, 2020

CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting.
CoRR, 2020

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness.
Proceedings of the Machine Learning for Health Workshop, 2020

Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Author Correction: Human-machine partnership with artificial intelligence for chest radiograph diagnosis.
npj Digit. Medicine, 2019

Human-machine partnership with artificial intelligence for chest radiograph diagnosis.
npj Digit. Medicine, 2019

Automated abnormality detection in lower extremity radiographs using deep learning.
Nat. Mach. Intell., 2019

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Know What You Don't Know: Unanswerable Questions for SQuAD.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs.
CoRR, 2017

Malaria Likelihood Prediction By Effectively Surveying Households Using Deep Reinforcement Learning.
CoRR, 2017

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning.
CoRR, 2017

Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks.
CoRR, 2017

2016
SQuAD: 100, 000+ Questions for Machine Comprehension of Text.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Augur: Mining Human Behaviors from Fiction to Power Interactive Systems.
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 2016

2015
Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving.
CoRR, 2015

An Empirical Evaluation of Deep Learning on Highway Driving.
CoRR, 2015

Text Mining Emergent Human Behaviors for Interactive Systems.
Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, 2015


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