Pranav Rajpurkar
Orcid: 0000-0002-8030-3727
According to our database1,
Pranav Rajpurkar
authored at least 80 papers
between 2015 and 2024.
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Bibliography
2024
RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models.
CoRR, 2024
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges.
CoRR, 2024
HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation.
CoRR, 2024
CoRR, 2024
ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics.
CoRR, 2024
Uncovering Knowledge Gaps in Radiology Report Generation Models through Knowledge Graphs.
CoRR, 2024
Towards Non-invasive and Personalized Management of Breast Cancer Patients from Multiparametric MRI via A Large Mixture-of-Modality-Experts Model.
CoRR, 2024
Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation.
CoRR, 2024
FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores.
CoRR, 2024
2023
Patterns, September, 2023
Predicting patient decompensation from continuous physiologic monitoring in the emergency department.
npj Digit. Medicine, 2023
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
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
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
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
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
2022
Nat. Mac. Intell., October, 2022
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
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
2021
Automated coronary calcium scoring using deep learning with multicenter external validation.
npj Digit. Medicine, 2021
J. Biomed. Informatics, 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
CoRR, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
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
Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021
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
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
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
CoRR, 2017
CoRR, 2017
2016
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 2016
2015
Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, 2015