A full list of publications available here.
Li, S., Shang, Y., Wang, Z., Wu, Q., Hong, C., Ning, Y., Miao, D., ... & Liu, N. (2024). Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data. arXiv preprint arXiv:2403.05229. https://arxiv.org/abs/2403.05229
Teo, Z. L., Jin, L., Liu, N., Li, S., Miao, D., Zhang, X., ... & Ting, D. S. W. (2024). Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture. Cell Reports Medicine. https://doi.org/10.1016/j.xcrm.2024.101419
Li, S., Miao, D., Wu, Q., Hong, C., Agostino, D., Li, X., ... & Liu, N. (2023). Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches. arXiv preprint arXiv:2311.03417. https://arxiv.org/abs/2311.03417
Li, S., Ning, Y., Ong, M.E., Chakraborty, B., Hong, C., Xie, F., ... & Liu, N. (2023). FedScore: A privacy-preserving framework for federated scoring system development. Journal of Biomedical Informatics, Volume 146, 2023,104485, ISSN 1532-0464 https://doi.org/10.1016/j.jbi.2023.104485
Li, S., Liu, P., Nascimento, G. G., Wang, X., Leite, F. R. M., Chakraborty, B., ... & Liu, N. (2023). Federated and distributed learning applications for electronic health records and structured medical data: a scoping review. Journal of the American Medical Informatics Association, 30(12), 2041–2049. https://doi.org/10.1093/jamia/ocad170
Liu, M.*, Li, S.*, Yuan, H., Ong, M. E. H., Ning, Y., Xie, F., ... & Liu, N. (2023). Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. Artificial Intelligence in Medicine, 102587. https://doi.org/10.1016/j.artmed.2023.102587