Lungren, Matthew P.

Ethics of using and sharing clinical imaging data for artificial intelligence: a proposed framework

Larson, D. B., Magnus, D. C., Lungren, M. P., Shah, N. H., & Langlotz, C. P. (2020) · Radiology

Artificial Intelligence in Healthcare and EducationEthics in Clinical Research

Cited by 199

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

Rajpurkar, P., O’Connell, C., Schechter, A., Asnani, N., Li, J., Kiani, A., Ball, R. L., Mendelson, M., Maartens, G., van Hoving, D. J., et al. (2020) · npj Digital Medicine

COVID-19 diagnosis using AITuberculosis Research and Epidemiology

Cited by 137

Exploring scalable medical image encoders beyond text supervision

Pérez-García, F., Sharma, H., Bond-Taylor, S., Bouzid, K., Salvatelli, V., Ilse, M., Bannur, S., Castro, D. C., Schwaighofer, A., Lungren, M. P., et al. (2025) · Nature Machine Intelligence

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 115

Generating synthetic data for medical imaging

Koetzier, L. R., Wu, J., Mastrodicasa, D., Lutz, A., Chung, M., Koszek, W. A., Pratap, J., Chaudhari, A. S., Rajpurkar, P., Lungren, M. P., et al. (2024) · Radiology

Artificial Intelligence in Healthcare and EducationGenerative Adversarial Networks and Image Synthesis

Cited by 111

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

Smit, A., Jain, S., Rajpurkar, P., Pareek, A., Ng, A. Y., & Lungren, M. P. (2020) · arXiv

Multimodal Machine Learning ApplicationsMachine Learning in Healthcare

Cited by 103

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Yildirim, N., Richardson, H., Wetscherek, M. T., Bajwa, J., Jacob, J., Pinnock, M. A., Harris, S., Coelho De Castro, D., Bannur, S., Hyland, S., et al. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 82

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

Cohen, J. P., Viviano, J. D., Bertin, P., Morrison, P., Torabian, P., Guarrera, M., Lungren, M. P., Chaudhari, A., Brooks, R., Hashir, M., et al. (2021) · arXiv

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 82

Deep learning evaluation of biomarkers from echocardiogram videos

Hughes, J. W., Yuan, N., He, B., Ouyang, J., Ebinger, J., Botting, P., Lee, J., Theurer, J., Tooley, J. E., Nieman, K., et al. (2021) · EBioMedicine

Artificial Intelligence in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 71

Holistic evaluation of large language models for medical tasks with MedHELM

Bedi, S., Cui, H., Fuentes, M., Unell, A., Wornow, M., Banda, J. M., Kotecha, N., Keyes, T., Mai, Y., Oez, M., et al. (2026) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 59

A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings

Zambrano Chaves, J. M., Huang, S.-C., Xu, Y., Xu, H., Usuyama, N., Zhang, S., Wang, F., Xie, Y., Khademi, M., Yang, Z., et al. (2025) · Nature Communications

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 45

Deep learning to detect left ventricular structural abnormalities in chest X-rays

Bhave, S., Rodriguez, V., Poterucha, T., Mutasa, S., Aberle, D., Capaccione, K. M., Chen, Y., Dsouza, B., Dumeer, S., Goldstein, J., et al. (2024) · European Heart Journal

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 38

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Jain, S., Agrawal, A., Saporta, A., Truong, S. Q., Nguyen Duong, D., Bui, T., Chambon, P., Lungren, M., Ng, A., Langlotz, C., et al. (2021) · PhysioNet

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 34

MAIRA-2: Grounded Radiology Report Generation

Bannur, S., Bouzid, K., Castro, D. C., Schwaighofer, A., Thieme, A., Bond-Taylor, S., Ilse, M., Pérez-García, F., Salvatelli, V., Sharma, H., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 19

CheXstray: A Real-Time Multi-Modal Monitoring Workflow for Medical Imaging AI

Merkow, J., Soin, A., Long, J., Cohen, J. P., Saligrama, S., Bridge, C., Yang, X., Kaiser, S., Borg, S., Tarapov, I., et al. (2023) · Lecture Notes in Computer Science

Artificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI

Cited by 13

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Thieme, A., Rajamohan, A., Cooper, B., Groombridge, H., Simister, R., Wong, B., Woznitza, N., Pinnock, M. A., Wetscherek, M. T., Morrison, C., et al. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

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The Illusion of Readiness in Health AI

Gu, Y., Fu, J., Liu, X., Valanarasu, J. M. J., Codella, N. C., Tan, R., Liu, Q., Jin, Y., Zhang, S., Wang, J., et al. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationAdversarial Robustness in Machine Learning

Cited by 1