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Marginal clustered multistate models for longitudinal progressive processes with informative cluster size.

AI4PH Authors: Sean Feng (Scholar), Aya Mitani (Mentor)
Reference: Feng, S. X., & Mitani, A. A. (2024). Marginal clustered multistate models for longitudinal progressive processes with informative cluster size. Statistical Analysis and Data Mining: The ASA Data Science Journal, 17(2), e11668. https://doi.org/10.1002/sam.11668

Lifecycles, pipelines, and value chains: Toward a focus on events in responsible artificial intelligence for health.

AI4PH Authors: Joseph Donia (Scholar), Jay Shaw (Mentor)
Reference: Donia, J., Oyefeso, L., Embuldeniya, G., Whyne, C., Burns, D., Boyer, P., Razmjou, H., & Shaw, J. A. (2024). Lifecycles, pipelines, and value chains: Toward a focus on events in responsible artificial intelligence for health. AI and Ethics. https://doi.org/10.1007/s43681-024-00594-4

The association between total social exposure and incident multimorbidity: A population-based cohort study.

AI4PH Authors: Ingrid Giesinger (Scholar), Laura Rosella (Co-PI, NPA)
Giesinger, I., Buajitti, E., Siddiqi, A., Smith, P. M., Krishnan, R. G., & Rosella, L. C. (2024). The association between total social exposure and incident multimorbidity: A population-based cohort study. SSM-Population Health, 101743. https://doi.org/10.1016/j.ssmph.2024.101743

TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare

AI4PH Authors: He Zhu (Scholar), David Buckeridge (Co-PI)  
Reference:  Song, Z., Lu, Q., Xu, H., Zhu, H., Buckeridge, D., & Li, Y. (2024). TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare. In Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB '24) (Article 16, pp. 1–10). Association for Computing Machinery.

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