Peng, Yifan

ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., & Summers, R. M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

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

Cited by 4,616

Opportunities and obstacles for deep learning in biology and medicine

Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., et al. (2018) · Journal of The Royal Society Interface

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 2,310

Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets

Peng, Y., Yan, S., & Lu, Z. (2019) · Proceedings of the 18th BioNLP Workshop and Shared Task

Topic ModelingMachine Learning in Healthcare

Cited by 899

A framework for human evaluation of large language models in healthcare derived from literature review.

Tam, T. Y. C., Sivarajkumar, S., Kapoor, S., Stolyar, A. V., Polanska, K., McCarthy, K. R., Osterhoudt, H., Wu, X., Visweswaran, S., Fu, S., et al. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 424

Evaluating large language models on medical evidence summarization

Tang, L., Sun, Z., Idnay, B., Nestor, J. G., Soroush, A., Elias, P. A., Xu, Z., Ding, Y., Durrett, G., Rousseau, J. F., et al. (2023) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 423

Evaluating Large Language Models on Medical Evidence Summarization

Tang, L., Sun, Z., Idnay, B., Nestor, J. G., Soroush, A., Elias, P. A., Xu, Z., Ding, Y., Durrett, G., Rousseau, J., et al. (2023) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 423

MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

Johnson, A. E. W., Pollard, T. J., Greenbaum, N. R., Lungren, M. P., Deng, C.-Y., Peng, Y., Lu, Z., Mark, R. G., Berkowitz, S. J., & Horng, S. (2019) · arXiv

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 269

Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task

Wei, C.-H., Peng, Y., Leaman, R., Davis, A. P., Mattingly, C. J., Li, J., Wiegers, T. C., & Lu, Z. (2016) · Database

Biomedical Text Mining and OntologiesAdvanced Text Analysis Techniques

Cited by 198

NegBio: a high-performance tool for negation and uncertainty detection in radiology reports

Peng, Y., Wang, X., Lu, L., Bagheri, M., Summers, R., & Lu, Z. (2017) · arXiv

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 175

Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine

Jin, Q., Chen, F., Zhou, Y., Xu, Z., Cheung, J. M., Chen, R., Summers, R. M., Rousseau, J. F., Ni, P., Landsman, M. J., et al. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 146

Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare

Oniani, D., Hilsman, J., Peng, Y., Poropatich, R. K., Pamplin, J. C., Legault, G. L., & Wang, Y. (2023) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 143

Large language models in biomedicine and health: current research landscape and future directions

Lu, Z., Peng, Y., Cohen, T., Ghassemi, M., Weng, C., & Tian, S. (2024) · Journal of the American Medical Informatics Association

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 92

Leveraging long context in retrieval augmented language models for medical question answering

Zhang, G., Xu, Z., Jin, Q., Chen, F., Fang, Y., Liu, Y., Rousseau, J. F., Xu, Z., Lu, Z., Weng, C., et al. (2025) · npj Digital Medicine

Topic ModelingInformation Retrieval and Search Behavior

Cited by 81

A scoping review on multimodal deep learning in biomedical images and texts

Sun, Z., Lin, M., Zhu, Q., Xie, Q., Wang, F., Lu, Z., & Peng, Y. (2023) · Journal of Biomedical Informatics

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 69

AI-generated text may have a role in evidence-based medicine

Peng, Y., Rousseau, J. F., Shortliffe, E. H., & Weng, C. (2023) · Nature Medicine

Artificial Intelligence in Healthcare and EducationBiomedical Text Mining and Ontologies

Cited by 64

miRTex: A Text Mining System for miRNA-Gene Relation Extraction

Li, G., Ross, K. E., Arighi, C. N., Peng, Y., Wu, C. H., & Vijay-Shanker, K. (2015) · PLOS Computational Biology

Biomedical Text Mining and OntologiesMicroRNA in disease regulation

Cited by 61

Faithful AI in Medicine: A Systematic Review with Large Language Models and Beyond

Xie, Q., Schenck, E. J., Yang, H. S., Chen, Y., Peng, Y., & Wang, F. (2023) · medRxiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 57

MIMIC-CXR-JPG - chest radiographs with structured labels

Johnson, A., Lungren, M., Peng, Y., Lu, Z., Mark, R., Berkowitz, S., & Horng, S. (2024) · PhysioNet

Multimodal Machine Learning ApplicationsCOVID-19 diagnosis using AI

Cited by 46

Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness

Zhang, G., Jin, Q., Jered McInerney, D., Chen, Y., Wang, F., Cole, C. L., Yang, Q., Wang, Y., Malin, B. A., Peleg, M., et al. (2024) · Journal of Biomedical Informatics

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 40

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias

Yu, Z., Peng, C., Yang, X., Dang, C., Adekkanattu, P., Gopal Patra, B., Peng, Y., Pathak, J., Wilson, D. L., Chang, C.-Y., et al. (2024) · Journal of Biomedical Informatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 37

Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports

Zhu, Q., Mathai, T. S., Mukherjee, P., Peng, Y., Summers, R. M., & Lu, Z. (2023) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 36

Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment

Ji, Z., Shaikh, M. A., Moukheiber, D., Srihari, S. N., Peng, Y., & Gao, M. (2021) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 21

Representing and utilizing clinical textual data for real world studies: An OHDSI approach

Keloth, V. K., Banda, J. M., Gurley, M., Heider, P. M., Kennedy, G., Liu, H., Liu, F., Miller, T., Natarajan, K., V Patterson, O., et al. (2023) · Journal of Biomedical Informatics

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 16

DeepSeek is open-access and the next AI disrupter for radiology

Peng, Y., Chen, Q., & Shih, G. (2025) · Radiology Advances

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 15