Treatment Effect Modelling and Treatment Recommendation

We design machine learning and reinforcement learning models to estimate treatment effects and recommend personalised interventions. By modelling longitudinal outcomes and counterfactuals, we enable adaptive, evidence-based care strategies.

Publications

Ghosheh, Ghadeer O., Moritz Gögl, and Tingting Zhu. "A perspective on individualized treatment effects estimation from time-series health data." Journal of the American Medical Informatics Association (2025): ocae323. paper
Yuan, Kevin, et al. "Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections." Journal of Infection 90.2 (2025): 106388. paper
Luo, Zhiyao, et al. "Position: reinforcement learning in dynamic treatment regimes needs critical reexamination." Proceedings of the 41st International Conference on Machine Learning. 2024. paper, code