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2. Statistical Methods for Learning Patients Heterogeneity and Treatment Effects to Achieve Precision Medicine
3. The Joint Modeling of Longitudinal Covariates and Censored Quantile Regression for Health Applications
4. Analysis Approaches for Wearable Device Data
5. Bayesian Modeling in Personalized Medicine with Applications to N-of-1 Trials
6. Causal Mediation Analysis for Effect Heterogeneity
7. Dynamic graphical models and curve registration for high-dimensional time course data
8. Regularized Greedy Gradient Q-Learning with Mobile Health Applications
9. Statistical and Machine Learning Methods for Pattern Identification in Environmental Mixtures
10. Statistical and Machine Learning Methods for Precision Medicine
11. Statistical Methods for Modeling Progression and Learning Mechanisms of Neuropsychiatric Disorders
12. Topics in Bayesian Design and Analysis for Sampling
13. Effect modification by socioeconomic conditions on the effects of prescription opioid supply on drug poisoning deaths in the United States
14. Optimal Treatment Regimes for Personalized Medicine and Mobile Health
15. Predictors of Barriers to Medical Care Among People Living with HIV in New York City: Changes from 2002 to 2017
16. Statistical Issues in Platform Trials with a Shared Control Group
17. Bayesian Modeling of Latent Heterogeneity in Complex Survey Data and Electronic Health Records
18. Functional data analytics for wearable device and neuroscience data
19. Machine Learning Methods for Personalized Medicine Using Electronic Health Records
20. Modern Statistical/Machine Learning Techniques for Bio/Neuro-imaging Applications
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