CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. - Pranav Rajpurkar; Jeremy Irvin; Kaylie Zhu; Brandon Yang; Hershel Mehta; Tony Duan; Daisy Yi Ding; Aarti Bagul; Curtis P. Langlotz; Katie S. Shpanskaya; Matthew P. Lungren; Andrew Y. Ng (CoRR, 2017)

MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. - Pranav Rajpurkar; Jeremy Irvin; Aarti Bagul; Daisy Yi Ding; Tony Duan; Hershel Mehta; Brandon Yang; Kaylie Zhu; Dillon Laird; Robyn L. Ball; Curtis P. Langlotz; Katie S. Shpanskaya; et al. (CoRR, 2017)

Overview of ImageCLEF 2018 Medical Domain Visual Question Answering Task. - Sadid A. Hasan; Yuan Ling; Oladimeji Farri; Joey Liu; Henning Müller; Matthew P. Lungren (CLEF (Working Notes), 2018)

Overview of ImageCLEF 2018: Challenges, Datasets and Evaluation. - Bogdan Ionescu; Henning Müller; Mauricio Villegas; Alba Garcia Seco de Herrera; Carsten Eickhoff; Vincent Andrearczyk; Yashin Dicente Cid; Vitali Liauchuk; Vassili Kovalev; Sadid A. Hasan; Yuan Ling; Oladimeji Farri; et al. (CLEF, 2018)

Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort. - Imon Banerjee; Matthew C. Chen; Matthew P. Lungren; Daniel L. Rubin (J. Biomed. Informatics, 2018)

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. - Jeremy Irvin; Pranav Rajpurkar; Michael Ko; Yifan Yu 005; Silviana Ciurea-Ilcus; Christopher Chute; Henrik Marklund; Behzad Haghgoo; Robyn L. Ball; Katie S. Shpanskaya; Jayne Seekins; David A. Mong; et al. (AAAI, 2019)

Prediction of Imaging Outcomes from Electronic Health Records: Pulmonary Embolism Case-Study. - Imon Banerjee; Miji Sofela; Timothy Amrhein; Daniel L. Rubin; Roham Zamanian; Matthew P. Lungren (AMIA, 2019)

Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification. - Imon Banerjee; Yuan Ling; Matthew C. Chen; Sadid A. Hasan; Curtis P. Langlotz; Nathaniel Moradzadeh; Brian E. Chapman; Timothy Amrhein; David A. Mong; Daniel L. Rubin; Oladimeji Farri; Matthew P. Lungren (Artif. Intell. Medicine, 2019)

MIMIC-CXR: A large publicly available database of labeled chest radiographs. - Alistair E. W. Johnson; Tom J. Pollard; Seth J. Berkowitz; Nathaniel R. Greenbaum; Matthew P. Lungren; Chih-ying Deng; Roger G. Mark; Steven Horng (CoRR, 2019)

Automated abnormality detection in lower extremity radiographs using deep learning. - Maya Varma; Mandy Lu; Rachel Gardner; Jared Dunnmon; Nishith Khandwala; Pranav Rajpurkar; Jin Long; Christopher Beaulieu; Katie S. Shpanskaya; Li Fei-Fei 001; Matthew P. Lungren; Bhavik N. Patel (Nat. Mach. Intell., 2019)

Human-machine partnership with artificial intelligence for chest radiograph diagnosis. - Bhavik N. Patel; Louis B. Rosenberg; Gregg Willcox; David Baltaxe; Mimi Lyons; Jeremy Irvin; Pranav Rajpurkar; Timothy Amrhein; Rajan Gupta; Safwan Halabi; Curtis P. Langlotz; Edward Lo; et al. (npj Digit. Medicine, 2019)

Author Correction: Human-machine partnership with artificial intelligence for chest radiograph diagnosis. - Bhavik N. Patel; Louis B. Rosenberg; Gregg Willcox; David Baltaxe; Mimi Lyons; Jeremy Irvin; Pranav Rajpurkar; Timothy Amrhein; Rajan Gupta; Safwan Halabi; Curtis P. Langlotz; Edward Lo; et al. (npj Digit. Medicine, 2019)

Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. - Akshay Smit; Saahil Jain; Pranav Rajpurkar; Anuj Pareek; Andrew Y. Ng; Matthew P. Lungren (EMNLP (1), 2020)

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. - Nick A. Phillips; Pranav Rajpurkar; Mark Sabini; Rayan Krishnan; Sharon Zhou; Anuj Pareek; Nguyet Minh Phu; Chris Wang; Mudit Jain; Du Nguyen Duong; Steven Q. H. Truong; Andrew Y. Ng; et al. (ML4H@NeurIPS, 2020)

CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting. - Pranav Rajpurkar; Anirudh Joshi; Anuj Pareek; Phil Chen; Amirhossein Kiani; Jeremy Irvin; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

Assessing Robustness to Noise: Low-Cost Head CT Triage. - Sarah M. Hooper; Jared A. Dunnmon; Matthew P. Lungren; Sanjiv Sam Gambhir; Christopher Ré; Adam S. Wang; Bhavik N. Patel (CoRR, 2020)

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. - Akshay Smit; Saahil Jain; Pranav Rajpurkar; Anuj Pareek; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. - Nick A. Phillips; Pranav Rajpurkar; Mark Sabini; Rayan Krishnan; Sharon Zhou; Anuj Pareek; Nguyet Minh Phu; Chris Wang; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays. - Pranav Rajpurkar; Anirudh Joshi; Anuj Pareek; Jeremy Irvin; Andrew Y. Ng; Matthew P. Lungren (CoRR, 2020)

PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. - Shih-Cheng Huang; Tanay Kothari; Imon Banerjee; Christopher Chute; Robyn L. Ball; Norah Borus; Andrew Huang; Bhavik N. Patel; Pranav Rajpurkar; Jeremy Irvin; Jared Dunnmon; Joseph Bledsoe; et al. (npj Digit. Medicine, 2020)

Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. - Shih-Cheng Huang; Tanay Kothari; Imon Banerjee; Christopher Chute; Robyn L. Ball; Norah Borus; Andrew Huang; Bhavik N. Patel; Pranav Rajpurkar; Jeremy Irvin; Jared Dunnmon; Joseph Bledsoe; et al. (npj Digit. Medicine, 2020)

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines. - Shih-Cheng Huang; Anuj Pareek; Saeed Seyyedi; Imon Banerjee; Matthew P. Lungren (npj Digit. Medicine, 2020)

CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV. - Pranav Rajpurkar; Chloe O'Connell; Amit Schechter; Nishit Asnani; Jason Li; Amirhossein Kiani; Robyn L. Ball; Marc Mendelson; Gary Maartens; Daniël J. van Hoving; Rulan Griesel; Andrew Y. Ng; et al. (npj Digit. Medicine, 2020)

Cross-Modal Data Programming Enables Rapid Medical Machine Learning. - Jared A. Dunnmon; Alexander J. Ratner; Khaled Saab 002; Nishith Khandwala; Matthew Markert; Hersh Sagreiya; Roger E. Goldman; Christopher Lee-Messer; Matthew P. Lungren; Daniel L. Rubin; Christopher Ré (Patterns, 2020)

VisualCheXbert: addressing the discrepancy between radiology report labels and image labels. - Saahil Jain; Akshay Smit; Steven Q. H. Truong; Chanh D. T. Nguyen; Minh-Thanh Huynh; Mudit Jain; Victoria A. Young; Andrew Y. Ng; Matthew P. Lungren; Pranav Rajpurkar (CHIL, 2021)

CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings. - Pranav Rajpurkar; Anirudh Joshi; Anuj Pareek; Andrew Y. Ng; Matthew P. Lungren (CHIL, 2021)

GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition. - Shih-Cheng Huang; Liyue Shen; Matthew P. Lungren; Serena Yeung (ICCV, 2021)

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays. - Joseph Paul Cohen; Rupert Brooks; Sovann En; Evan Zucker; Anuj Pareek; Matthew P. Lungren; Akshay Chaudhari (MIDL, 2021)

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. - Saahil Jain; Ashwin Agrawal; Adriel Saporta; Steven Q. H. Truong; Du Nguyen Duong; Tan Bui; Pierre J. Chambon; Yuhao Zhang 004; Matthew P. Lungren; Andrew Y. Ng; Curtis P. Langlotz; Pranav Rajpurkar (NeurIPS Datasets and Benchmarks, 2021)

Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays. - Joseph Paul Cohen; Rupert Brooks; Sovann En; Evan Zucker; Anuj Pareek; Matthew P. Lungren; Akshay Chaudhari (CoRR, 2021)

Structured dataset documentation: a datasheet for CheXpert. - Christian Garbin; Pranav Rajpurkar; Jeremy Irvin; Matthew P. Lungren; Oge Marques (CoRR, 2021)

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning. - Grant Duffy; Paul P. Cheng; Neal Yuan; Bryan He; Alan C. Kwan; Matthew J. Shun-Shin; Kevin M. Alexander; Joseph Ebinger; Matthew P. Lungren; Florian Rader; David H. Liang; Ingela Schnittger; et al. (CoRR, 2021)

Production-level Open Source Privacy Preserving Inference in Medical Imaging. - Arjun Soin; Pratik Bhatu; Rohit Takhar; Nishanth Chandran; Divya Gupta 001; Javier Alvarez-Valle; Rahul Sharma 001; Vidur Mahajan; Matthew P. Lungren (CoRR, 2021)

Reading Race: AI Recognises Patient's Racial Identity In Medical Images. - Imon Banerjee; Ananth Reddy Bhimireddy; John L. Burns; Leo Anthony Celi; Li-Ching Chen; Ramon Correa; Natalie Dullerud; Marzyeh Ghassemi; Shih-Cheng Huang; Po-Chih Kuo; Matthew P. Lungren; Lyle J. Palmer; et al. (CoRR, 2021)

OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations. - Anirudh Joshi; Sabri Eyuboglu; Shih-Cheng Huang; Jared Dunnmon; Arjun Soin; Guido A. Davidzon; Akshay Chaudhari; Matthew P. Lungren (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. - Michael Fitzke; Derick Whitley; Wilson Yau; Fernando Rodrigues Jr; Vladimir Fadeev; Cindy Bacmeister; Chris Carter; Jeffrey Edwards; Matthew P. Lungren; Mark Parkinson (CoRR, 2021)

Active label cleaning: Improving dataset quality under resource constraints. - Melanie Bernhardt; Daniel C. Castro; Ryutaro Tanno; Anton Schwaighofer; Kerem Can Tezcan; Miguel Monteiro; Shruthi Bannur; Matthew P. Lungren; Aditya V. Nori; Ben Glocker; Javier Alvarez-Valle; Ozan Oktay (CoRR, 2021)

fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data. - Ruiyang Zhao; Burhaneddin Yaman; Yuxin Zhang; Russell Stewart; Austin Dixon; Florian Knoll; Zhengnan Huang; Yvonne W. Lui; Michael S. Hansen; Matthew P. Lungren (CoRR, 2021)

End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction. - Ruiyang Zhao; Yuxin Zhang; Burhaneddin Yaman; Matthew P. Lungren; Michael S. Hansen (CoRR, 2021)

RapidRead: Global Deployment of State-of-the-art Radiology AI for a Large Veterinary Teleradiology Practice. - Michael Fitzke; Conrad Stack; Andre Dourson; Rodrigo M. B. Santana; Diane Wilson; Lisa Ziemer; Arjun Soin; Matthew P. Lungren; Paul Fisher; Mark Parkinson (CoRR, 2021)

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR. - Yuyin Zhou; Shih-Cheng Huang; Jason Alan Fries; Alaa Youssef; Timothy J. Amrhein; Marcello Chang; Imon Banerjee; Daniel L. Rubin; Lei Xing 001; Nigam Shah; Matthew P. Lungren (CoRR, 2021)

Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions. - Tina Hernandez-Boussard; Matthew P. Lungren; Nigam Shah (J. Am. Medical Informatics Assoc., 2021)

Corrigendum: Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions. - Tina Hernandez-Boussard; Matthew P. Lungren; Nigam Shah (J. Am. Medical Informatics Assoc., 2021)

Automated coronary calcium scoring using deep learning with multicenter external validation. - David Eng; Christopher Chute; Nishith Khandwala; Pranav Rajpurkar; Jin Long; Sam Shleifer; Mohamed H. Khalaf; Alexander T. Sandhu; Fátima Rodriguez; David J. Maron; Saeed Seyyedi; Daniele Marin; et al. (npj Digit. Medicine, 2021)

Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging. - Riccardo Fogliato; Shreya Chappidi; Matthew P. Lungren; Paul Fisher; Diane Wilson; Michael Fitzke; Mark Parkinson; Eric Horvitz; Kori Inkpen; Besmira Nushi (FAccT, 2022)

TorchXRayVision: A library of chest X-ray datasets and models. - Joseph Paul Cohen; Joseph D. Viviano; Paul Bertin; Paul Morrison; Parsa Torabian; Matteo Guarrera; Matthew P. Lungren; Akshay Chaudhari; Rupert Brooks; Mohammad Hashir; Hadrien Bertrand (MIDL, 2022)

Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation. - Yuhui Zhang; Shih-Cheng Huang; Zhengping Zhou; Matthew P. Lungren; Serena Yeung (ML4H@NeurIPS, 2022)

CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI. - Arjun Soin; Jameson Merkow; Jin Long; Joseph Paul Cohen; Smitha Saligrama; Stephen Kaiser; Steven Borg; Ivan Tarapov; Matthew P. Lungren (CoRR, 2022)

Learning to Bootstrap for Combating Label Noise. - Yuyin Zhou; Xianhang Li; Fengze Liu; Xuxi Chen; Lequan Yu; Cihang Xie; Matthew P. Lungren; Lei Xing 001 (CoRR, 2022)

Current State of Community-Driven Radiological AI Deployment in Medical Imaging. - Vikash Gupta; Barbaros Selnur Erdal; Carolina Ramirez; Ralf Floca; Laurence Jackson; Brad W. Genereaux; Sidney Bryson; Christopher P. Bridge; Jens Kleesiek; Felix Nensa; Rickmer Braren; Khaled Younis; et al. (CoRR, 2022)

Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. - Andre Esteva; Jean Feng; Douwe van der Wal; Shih-Cheng Huang; Jeffry P. Simko; Sandy Devries; Emmalyn Chen; Edward M. Schaeffer; Todd M. Morgan; Yilun Sun; Amirata Ghorbani; Nikhil Naik 002; et al. (npj Digit. Medicine, 2022)

Digital health technology-specific risks for medical malpractice liability. - Simon P. Rowland; J. Edward Fitzgerald; Matthew P. Lungren; Elizabeth Lee; Zach Harned; Alison H. McGregor (npj Digit. Medicine, 2022)

Automatic Lung Nodule Segmentation and Intra-Nodular Heterogeneity Image Generation. - Jiangdian Song; Shih-Cheng Huang; Brendan Kelly; Guanqun Liao; Jingyun Shi; Ning Wu; Weimin Li 003; Zaiyi Liu; Lei Cui 008; Matthew P. Lungren; Michael E. Moseley; Peng Gao; et al. (IEEE J. Biomed. Health Informatics, 2022)

Benchmarking saliency methods for chest X-ray interpretation. - Adriel Saporta; Xiaotong Gui; Ashwin Agrawal; Anuj Pareek; Steven Q. H. Truong; Chanh D. T. Nguyen; Van Doan Ngo; Jayne Seekins; Francis G. Blankenberg; Andrew Y. Ng; Matthew P. Lungren; Pranav Rajpurkar (Nat. Mac. Intell., 2022)

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. - Shruthi Bannur; Stephanie L. Hyland; Qianchu Liu; Fernando Pérez-García; Maximilian Ilse; Daniel C. Castro; Benedikt Boecking; Harshita Sharma; Kenza Bouzid; Anja Thieme; Anton Schwaighofer; Maria Wetscherek; et al. (CVPR, 2023)

Taking Off with AI: Lessons from Aviation for Healthcare. - Elizabeth Bondi-Kelly; Thomas Hartvigsen; Lindsay M. Sanneman; Swami Sankaranarayanan; Zach Harned; Grace Wickerson; Judy Wawira Gichoya; Lauren Oakden-Rayner; Leo Anthony Celi; Matthew P. Lungren; Julie A. Shah; Marzyeh Ghassemi (EAAMO, 2023)

Exploring the Boundaries of GPT-4 in Radiology. - Qianchu Liu; Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Maria Wetscherek; Robert Tinn; Harshita Sharma; Fernando Pérez-García; Anton Schwaighofer; Pranav Rajpurkar; Sameer Tajdin Khanna; et al. (EMNLP, 2023)

CheXstray: A Real-Time Multi-Modal Monitoring Workflow for Medical Imaging AI. - Jameson Merkow; Arjun Soin; Jin Long; Joseph Paul Cohen; Smitha Saligrama; Christopher P. Bridge; Xiyu Yang; Stephen Kaiser; Steven Borg; Ivan Tarapov; Matthew P. Lungren (MICCAI (3), 2023)

INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms. - Shih-Cheng Huang; Zepeng Huo; Ethan Steinberg; Chia-Chun Chiang; Curtis P. Langlotz; Matthew P. Lungren; Serena Yeung; Nigam Shah; Jason Alan Fries (NeurIPS, 2023)

Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing. - Sheng Zhang 012; Yanbo Xu; Naoto Usuyama; Jaspreet Bagga; Robert Tinn; Sam Preston; Rajesh Rao; Mu Wei; Naveen Valluri; Cliff Wong; Matthew P. Lungren; Tristan Naumann; et al. (CoRR, 2023)

The Effect of Counterfactuals on Reading Chest X-rays. - Joseph Paul Cohen; Rupert Brooks; Sovann En; Evan Zucker; Anuj Pareek; Matthew P. Lungren; Akshay Chaudhari (CoRR, 2023)

Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery. - Debadutta Dash; Rahul Thapa; Juan M. Banda; Akshay Swaminathan; Morgan Cheatham; Mehr Kashyap; Nikesh Kotecha; Jonathan H. Chen; Saurabh Gombar; Lance Downing; Rachel Pedreira; Ethan Goh; et al. (CoRR, 2023)

3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers. - Jieneng Chen; Jieru Mei; Xianhang Li; Yongyi Lu; Qihang Yu; Qingyue Wei; Xiangde Luo; Yutong Xie 001; Ehsan Adeli 001; Yan Wang 033; Matthew P. Lungren; Lei Xing 001; et al. (CoRR, 2023)

BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys. - Yu Gu 017; Jianwei Yang; Naoto Usuyama; Chunyuan Li; Sheng Zhang 012; Matthew P. Lungren; Jianfeng Gao 001; Hoifung Poon (CoRR, 2023)

INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis. - Shih-Cheng Huang; Zepeng Huo; Ethan Steinberg; Chia-Chun Chiang; Matthew P. Lungren; Curtis P. Langlotz; Serena Yeung; Nigam H. Shah; Jason A. Fries (CoRR, 2023)

MAIRA-1: A specialised large multimodal model for radiology report generation. - Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Mercy Ranjit; Anton Schwaighofer; Fernando Pérez-García; Valentina Salvatelli; Shaury Srivastav; Anja Thieme; Noel Codella; Matthew P. Lungren; et al. (CoRR, 2023)

3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology. - Asma Ben Abacha; Alberto Santamaría-Pang; Ho Hin Lee; Jameson Merkow; Qin Cai; Surya Teja Devarakonda; Abdullah Islam; Julia Gong; Matthew P. Lungren; Thomas Lin; Noel C. F. Codella; Ivan Tarapov (CoRR, 2023)

Author Correction: Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials. - Andre Esteva; Jean Feng; Douwe van der Wal; Shih-Cheng Huang; Jeffry P. Simko; Sandy Devries; Emmalyn Chen; Edward M. Schaeffer; Todd M. Morgan; Yilun Sun; Amirata Ghorbani; Nikhil Naik 002; et al. (npj Digit. Medicine, 2023)

Self-supervised learning for medical image classification: a systematic review and implementation guidelines. - Shih-Cheng Huang; Anuj Pareek; Malte E. K. Jensen; Matthew P. Lungren; Serena Yeung; Akshay S. Chaudhari (npj Digit. Medicine, 2023)

MAIRA at RRG24: A specialised large multimodal model for radiology report generation. - Shaury Srivastav; Mercy Ranjit; Fernando Pérez-García; Kenza Bouzid; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Harshita Sharma; Maximilian Ilse; Valentina Salvatelli; Sam Bond-Taylor; Fabian Falck; et al. (BioNLP@ACL, 2024)

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology. - Nur Yildirim; Hannah Richardson; Maria Teodora Wetscherek; Junaid Bajwa; Joseph Jacob; Mark Ames Pinnock; Stephen Harris; Daniel Coelho de Castro; Shruthi Bannur; Stephanie L. Hyland; Pratik Ghosh; Mercy Ranjit; et al. (CHI, 2024)

L2B: Learning to Bootstrap Robust Models for Combating Label Noise. - Yuyin Zhou; Xianhang Li; Fengze Liu; Qingyue Wei; Xuxi Chen; Lequan Yu; Cihang Xie; Matthew P. Lungren; Lei Xing 001 (CVPR, 2024)

RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing. - Fernando Pérez-García; Sam Bond-Taylor; Pedro P. Sanchez; Boris van Breugel; Daniel C. Castro; Harshita Sharma; Valentina Salvatelli; Maria T. A. Wetscherek; Hannah Richardson; Matthew P. Lungren; Aditya V. Nori; Javier Alvarez-Valle; et al. (ECCV (12), 2024)

RAD-DINO: Exploring Scalable Medical Image Encoders Beyond Text Supervision. - Fernando Pérez-García; Harshita Sharma; Sam Bond-Taylor; Kenza Bouzid; Valentina Salvatelli; Maximilian Ilse; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Matthew P. Lungren; Maria Wetscherek; Noel Codella; et al. (CoRR, 2024)

Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging. - Juan Manuel Zambrano Chaves; Shih-Cheng Huang; Yanbo Xu; Hanwen Xu; Naoto Usuyama; Sheng Zhang 012; Fei Wang 060; Yujia Xie; Mahmoud Khademi; Ziyi Yang; Hany Hassan Awadalla; Julia Gong; et al. (CoRR, 2024)

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. - Anja Thieme; Abhijith Rajamohan; Benjamin Cooper; Heather Groombridge; Robert Simister; Barney Wong; Nicholas Woznitza; Mark Ames Pinnock; Maria Teodora Wetscherek; Cecily Morrison; Hannah Richardson; Fernando Pérez-García; et al. (CoRR, 2024)

MAIRA-2: Grounded Radiology Report Generation. - Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Anton Schwaighofer; Sam Bond-Taylor; Maximilian Ilse; Fernando Pérez-García; Valentina Salvatelli; Harshita Sharma; Felix Meissen; Mercy Ranjit; Shaury Srivastav; et al. (CoRR, 2024)

MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging. - Noel C. F. Codella; Ying Jin; Shrey Jain; Yu Gu; Ho Hin Lee; Asma Ben Abacha; Alberto Santamaría-Pang; Will Guyman; Naiteek Sangani; Sheng Zhang; Hoifung Poon; Stephanie L. Hyland; et al. (CoRR, 2024)

Scalable Drift Monitoring in Medical Imaging AI. - Jameson Merkow; Felix J. Dorfner; Xiyu Yang; Alexander Ersoy; Giridhar Dasegowda; Mannudeep K. Kalra; Matthew P. Lungren; Christopher P. Bridge; Ivan Tarapov (CoRR, 2024)

Ensuring useful adoption of generative artificial intelligence in healthcare. - Jenelle A. Jindal; Matthew P. Lungren; Nigam H. Shah (J. Am. Medical Informatics Assoc., 2024)

TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers. - Jieneng Chen; Jieru Mei; Xianhang Li; Yongyi Lu; Qihang Yu; Qingyue Wei; Xiangde Luo; Yutong Xie 001; Ehsan Adeli 001; Yan Wang 033; Matthew P. Lungren; Shaoting Zhang 001; et al. (Medical Image Anal., 2024)

Exploring scalable medical image encoders beyond text supervision. - Fernando Pérez-García; Harshita Sharma; Sam Bond-Taylor; Kenza Bouzid; Valentina Salvatelli; Maximilian Ilse; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Matthew P. Lungren; Maria Teodora Wetscherek; Noel Codella; et al. (Nat. Mac. Intell., 2025)

Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model Representations. - Ho Hin Lee; Alberto Santamaría-Pang; Jameson Merkov; Matthew P. Lungren; Ivan Tarapov (CoRR, 2025)

From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification. - Xue Li; Jameson Merkow; Noel C. F. Codella; Alberto Santamaría-Pang; Naiteek Sangani; Alexander Ersoy; Christopher Burt; John W. Garrett; Richard J. Bruce; Joshua D. Warner; Tyler J. Bradshaw; Ivan Tarapov; et al. (CoRR, 2025)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks. - Suhana Bedi; Hejie Cui; Miguel Fuentes; Alyssa Unell; Michael Wornow; Juan M. Banda; Nikesh Kotecha; Timothy Keyes; Yifan Mai 001; Mert Oez; Hao Qiu; Shrey Jain; et al. (CoRR, 2025)

Sequential Diagnosis with Language Models. - Harsha Nori; Mayank Daswani; Christopher Kelly; Scott M. Lundberg; Marco Túlio Ribeiro; Marc Wilson; Xiaoxuan Liu; Viknesh Sounderajah; Jonathan Carlson; Matthew P. Lungren; Bay Gross; Peter Hames; et al. (CoRR, 2025)

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology. - Anja Thieme; Abhijith Rajamohan; Benjamin Cooper; Heather Groombridge; Robert Simister; Barney Wong; Nicholas Woznitza; Mark A. Pinnock; Maria T. A. Wetscherek; Cecily Morrison; Hannah Richardson; Fernando Pérez-García; et al. (ACM Trans. Comput. Hum. Interact., 2025)