Corrigendum: Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions.

[BibT_eX]

[DOI]

Tina Hernandez-Boussard

Matthew P. Lungren

Nigam Shah

J. Am. Medical Informatics Assoc., 2021

Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions.

[BibT_eX]

[DOI]

Tina Hernandez-Boussard

Matthew P. Lungren

Nigam Shah

J. Am. Medical Informatics Assoc., 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

Michael Fitzke

Conrad Stack

Andre Dourson

Rodrigo M. B. Santana

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Active label cleaning: Improving dataset quality under resource constraints.

[BibT_eX]

[DOI]

CoRR, 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.

[BibT_eX]

[DOI]

Michael Fitzke

Derick Whitley

Wilson Yau

Fernando Rodrigues Jr

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Production-level Open Source Privacy Preserving Inference in Medical Imaging.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Structured dataset documentation: a datasheet for CheXpert.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings.

[BibT_eX]

[DOI]

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

VisualCheXbert: addressing the discrepancy between radiology report labels and image labels.

[BibT_eX]

[DOI]

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

2020

Cross-Modal Data Programming Enables Rapid Medical Machine Learning.

[BibT_eX]

[DOI]

Christopher Lee-Messer

Matthew P. Lungren

Daniel L. Rubin

Christopher Ré

Patterns, 2020

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

[BibT_eX]

[DOI]

npj Digit. Medicine, 2020

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2020

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

[BibT_eX]

[DOI]

npj Digit. Medicine, 2020

PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Assessing Robustness to Noise: Low-Cost Head CT Triage.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Health Workshop, 2020

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Joseph Mammarappallil

npj Digit. Medicine, 2019

Human-machine partnership with artificial intelligence for chest radiograph diagnosis.

[BibT_eX]

[DOI]

Joseph Mammarappallil

npj Digit. Medicine, 2019

Automated abnormality detection in lower extremity radiographs using deep learning.

[BibT_eX]

[DOI]

Nat. Mach. Intell., 2019

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

[BibT_eX]

[DOI]

Alistair E. W. Johnson

Tom J. Pollard

Seth J. Berkowitz

Nathaniel R. Greenbaum

CoRR, 2019

Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.

[BibT_eX]

[DOI]