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...
share
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...
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 ...
research
∙
01/11/2023
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Self-supervised learning in vision-language processing exploits semantic...
research
∙
02/09/2022
Learning to Bootstrap for Combating Label Noise
Deep neural networks are powerful tools for representation learning, but...
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 ...
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...
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 ...
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...
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 ...
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...
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...
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...
research
∙
07/21/2021
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Background: In medical imaging, prior studies have demonstrated disparat...
research
∙
07/21/2021
Multi-institution encrypted medical imaging AI validation without data sharing
Adoption of artificial intelligence medical imaging applications is ofte...
research
∙
06/28/2021
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
Extracting structured clinical information from free-text radiology repo...
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...
research
∙
05/07/2021
Structured dataset documentation: a datasheet for CheXpert
Billions of X-ray images are taken worldwide each year. Machine learning...
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...
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...
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...
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...
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...
research
∙
03/17/2020
Assessing Robustness to Noise: Low-Cost Head CT Triage
Automated medical image classification with convolutional neural network...
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...
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...
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...
research
∙
12/11/2017
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs
We introduce MURA, a large dataset of musculoskeletal radiographs contai...
research
∙
11/14/2017
