Matthew P. Lungren
Orcid: 0000-0002-8591-5861
According to our database1,
Matthew P. Lungren
authored at least 73 papers
between 2017 and 2024.
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Bibliography
2024
Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging.
CoRR, 2024
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology.
CoRR, 2024
CoRR, 2024
2023
Self-supervised learning for medical image classification: a systematic review and implementation guidelines.
npj Digit. Medicine, 2023
Author Correction: Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials.
npj Digit. Medicine, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
CoRR, 2023
BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys.
CoRR, 2023
CoRR, 2023
Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery.
CoRR, 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Nat. Mac. Intell., October, 2022
IEEE J. Biomed. Health Informatics, 2022
npj Digit. Medicine, 2022
Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials.
npj Digit. Medicine, 2022
CoRR, 2022
CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI.
CoRR, 2022
Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation.
Proceedings of the Machine Learning for Health, 2022
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
2021
Automated coronary calcium scoring using deep learning with multicenter external validation.
npj Digit. Medicine, 2021
Corrigendum: Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions.
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.
J. Am. Medical Informatics Assoc., 2021
RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR.
CoRR, 2021
RapidRead: Global Deployment of State-of-the-art Radiology AI for a Large Veterinary Teleradiology Practice.
CoRR, 2021
End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction.
CoRR, 2021
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data.
CoRR, 2021
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.
CoRR, 2021
OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations.
CoRR, 2021
CoRR, 2021
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning.
CoRR, 2021
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays.
CoRR, 2021
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.
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.
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.
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
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines.
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
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
CoRR, 2019
Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification.
Artif. Intell. Medicine, 2019
Prediction of Imaging Outcomes from Electronic Health Records: Pulmonary Embolism Case-Study.
Proceedings of the AMIA 2019, 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
Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort.
J. Biomed. Informatics, 2018
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2018
Proceedings of the Working Notes of CLEF 2018, 2018
2017
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs.
CoRR, 2017
CoRR, 2017