Huang, Shih-Cheng

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines

Huang, S.-C., Pareek, A., Seyyedi, S., Banerjee, I., & Lungren, M. P. (2020) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 934

AI recognition of patient race in medical imaging: a modelling study

Gichoya, J. W., Banerjee, I., Bhimireddy, A. R., Burns, J. L., Celi, L. A., Chen, L.-C., Correa, R., Dullerud, N., Ghassemi, M., Huang, S.-C., et al. (2022) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 611

GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition

Huang, S.-C., Shen, L., Lungren, M. P., & Yeung, S. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 489

Self-supervised learning for medical image classification: a systematic review and implementation guidelines

Huang, S.-C., Pareek, A., Jensen, M., Lungren, M. P., Yeung, S., & Chaudhari, A. S. (2023) · npj Digital Medicine

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Cited by 479

Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection

Huang, S.-C., Pareek, A., Zamanian, R., Banerjee, I., & Lungren, M. P. (2020) · Scientific Reports

Machine Learning in HealthcareRadiomics and Machine Learning in Medical Imaging

Cited by 246

Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials

Esteva, A., Feng, J., van der Wal, D., Huang, S.-C., Simko, J. P., DeVries, S., Chen, E., Schaeffer, E. M., Morgan, T. M., Sun, Y., et al. (2022) · npj Digital Medicine

Radiomics and Machine Learning in Medical ImagingAI in cancer detection

Cited by 217

Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging

Yan, R., Qu, L., Wei, Q., Huang, S.-C., Shen, L., Rubin, D. L., Xing, L., & Zhou, Y. (2023) · IEEE Transactions on Medical Imaging

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 183

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

CheXpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats

Chambon, P., Delbrouck, J.-B., Sounack, T., Huang, S.-C., Chen, Z., Varma, M., Truong, S. Q., Chuong, C. T., & Langlotz, C. P. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 8