Wong, Cliff

LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Li, C., Wong, C., Zhang, S., Usuyama, N., Liu, H., Yang, J., Naumann, T., Poon, H., & Gao, J. (2023) · Advances in Neural Information Processing Systems 36

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

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A whole-slide foundation model for digital pathology from real-world data

Xu, H., Usuyama, N., Bagga, J., Zhang, S., Rao, R., Naumann, T., Wong, C., Gero, Z., González, J., Gu, Y., et al. (2024) · Nature

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Li, C., Wong, C., Zhang, S., Usuyama, N., Liu, H., Yang, J., Naumann, T., Poon, H., & Gao, J. (2023) · arXiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

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A Multimodal Biomedical Foundation Model Trained from Fifteen Million Image–Text Pairs

Zhang, S., Xu, Y., Usuyama, N., Xu, H., Bagga, J., Tinn, R., Preston, S., Rao, R., Wei, M., Valluri, N., et al. (2025) · NEJM AI

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

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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

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Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology

Wong, C., Zhang, S., Gu, Y., Moung, C., Abel, J., Usuyama, N., Weerasinghe, R., Piening, B., Naumann, T., Bifulco, C., et al. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

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Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events

Gu, Y., Zhang, S., Usuyama, N., Woldesenbet, Y., Wong, C., Sanapathi, P., Wei, M., Valluri, N., Strandberg, E., Naumann, T., et al. (2023) · arXiv

Biomedical Text Mining and OntologiesTopic Modeling

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DocLens: Multi-aspect Fine-grained Medical Text Evaluation

Xie, Y., Zhang, S., Cheng, H., Liu, P., Gero, Z., Wong, C., Naumann, T., Poon, H., & Rose, C. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Biomedical Text Mining and OntologiesText Readability and Simplification

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Generative Medical Event Models Improve with Scale

Waxler, S., Blazek, P., White, D., Sneider, D., Chung, K., Nagarathnam, M., Williams, P., Voeller, H., Wong, K., Swanhorst, M., et al. (2025) · arXiv

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

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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

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