Matthew P. Lungren

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Featured Co-authors

Christopher Ré
125 publications
Sheng Zhang
73 publications
Lequan Yu
57 publications
Yuhao Zhang
55 publications
Marzyeh Ghassemi
54 publications
Haoran Zhang
48 publications
Andrew Y. Ng
46 publications
Eric Horvitz
45 publications
Cihang Xie
44 publications
Yuyin Zhou
41 publications
Joseph Paul Cohen
39 publications

research

∙ 04/26/2023

Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery

Despite growing interest in using large language models (LLMs) in health...

0 Debadutta Dash, et al. ∙

research

∙ 03/02/2023

Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing

Contrastive pretraining on parallel image-text data has attained great s...

0 Sheng Zhang, et al. ∙

research

∙ 02/08/2023

Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation

Given the prevalence of 3D medical imaging technologies such as MRI and ...

0 Yuhui Zhang, et al. ∙

research

∙ 01/11/2023

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Self-supervised learning in vision-language processing exploits semantic...

11 Shruthi Bannur, et al. ∙

research

∙ 02/09/2022

Learning to Bootstrap for Combating Label Noise

Deep neural networks are powerful tools for representation learning, but...

14 Yuyin Zhou, et al. ∙

research

∙ 02/06/2022

CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI

Rapidly expanding Clinical AI applications worldwide have the potential ...

0 Arjun Soin, et al. ∙

research

∙ 11/23/2021

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR

Despite the routine use of electronic health record (EHR) data by radiol...

31 Yuyin Zhou, et al. ∙

research

∙ 11/09/2021

RapidRead: Global Deployment of State-of-the-art Radiology AI for a Large Veterinary Teleradiology Practice

This work describes the development and real-world deployment of a deep ...

0 Michael Fitzke, et al. ∙

research

∙ 10/31/2021

TorchXRayVision: A library of chest X-ray datasets and models

TorchXRayVision is an open source software library for working with ches...

0 Joseph Paul Cohen, et al. ∙

research

∙ 09/23/2021

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction

Deep learning techniques have emerged as a promising approach to highly ...

0 Ruiyang Zhao, et al. ∙

research

∙ 09/08/2021

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data

Improving speed and image quality of Magnetic Resonance Imaging (MRI) vi...

0 Ruiyang Zhao, et al. ∙

research

∙ 08/17/2021

OncoPetNet: A Deep Learning based AI system for mitotic figure counting on H E stained whole slide digital images in a large veterinary diagnostic lab setting

Background: Histopathology is an important modality for the diagnosis an...

26 Michael Fitzke, et al. ∙

research

∙ 08/03/2021

OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations

FDG PET/CT imaging is a resource intensive examination critical for mana...

5 Anirudh Joshi, et al. ∙

research

∙ 07/21/2021

Reading Race: AI Recognises Patient's Racial Identity In Medical Images

Background: In medical imaging, prior studies have demonstrated disparat...

17 Imon Banerjee, et al. ∙

research

∙ 07/21/2021

Multi-institution encrypted medical imaging AI validation without data sharing

Adoption of artificial intelligence medical imaging applications is ofte...

0 Arjun Soin, et al. ∙

research

∙ 06/28/2021

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Extracting structured clinical information from free-text radiology repo...

17 Saahil Jain, et al. ∙

research

∙ 06/23/2021

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning

Left ventricular hypertrophy (LVH) results from chronic remodeling cause...

0 Grant Duffy, et al. ∙

research

∙ 05/07/2021

Structured dataset documentation: a datasheet for CheXpert

Billions of X-ray images are taken worldwide each year. Machine learning...

43 Christian Garbin, et al. ∙

research

∙ 02/23/2021

VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labels

Automatic extraction of medical conditions from free-text radiology repo...

11 Saahil Jain, et al. ∙

research

∙ 02/18/2021

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays

Motivation: Traditional image attribution methods struggle to satisfacto...

10 Joseph Paul Cohen, et al. ∙

research

∙ 02/17/2021

CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings

Recent advances in training deep learning models have demonstrated the p...

9 Pranav Rajpurkar, et al. ∙

research

∙ 07/13/2020

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

Clinical deployment of deep learning algorithms for chest x-ray interpre...

3 Nick A. Phillips, et al. ∙

research

∙ 04/20/2020

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

The extraction of labels from radiology text reports enables large-scale...

9 Akshay Smit, et al. ∙

research

∙ 03/17/2020

Assessing Robustness to Noise: Low-Cost Head CT Triage

Automated medical image classification with convolutional neural network...

3 Sarah M. Hooper, et al. ∙

research

∙ 02/26/2020

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

Although there have been several recent advances in the application of d...

1 Pranav Rajpurkar, et al. ∙

research

∙ 01/21/2019

MIMIC-CXR: A large publicly available database of labeled chest radiographs

Chest radiography is an extremely powerful imaging modality, allowing fo...

0 Alistair E. W. Johnson, et al. ∙

research

∙ 01/21/2019

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Large, labeled datasets have driven deep learning methods to achieve exp...

2 Jeremy Irvin, et al. ∙

research

∙ 12/11/2017

MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs

We introduce MURA, a large dataset of musculoskeletal radiographs contai...

0 Pranav Rajpurkar, et al. ∙

research

∙ 11/14/2017

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

We develop an algorithm that can detect pneumonia from chest X-rays at a...

0 Pranav Rajpurkar, et al. ∙

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