Statistics in Precision Health

Part I An Overview of Precision Health in the Big Data Era.- Overview of Precision Health: Past, Current, and Future.- A Selective Review of Individualized Decision Making.- Utilizing Wearable Devices to Improve Precision in Physical Activity Epidemiology: Sensors, Data and Analytic Methods.- Policy Learning for Individualized Treatment Regimes on Infinite Time Horizon.- Q-Learning Based Methods for Dynamic Treatment Regimes.- Personalized Medicine with Multiple Treatments.- Statistical Reinforcement Learning and Dynamic Treatment Regimes.- Part II New Advances in Statistical Methods of Precision Medicine and the Applications.-  Integrative Learning to Combine Individualized Treatment Rules from Multiple Randomized Trials.- Adaptive Semi-supervised Learning for Optimal Treatment Regime Estimation with Application to EMR Data.- Estimation and Inference for Individualized Treatment Rules Using Efficient Augmentation and Relaxation Learning.- Subgroup Analysis Using Doubly Robust Semiparametric Procedures.- A Selective Overview of Fusion Penalized Learning in Latent Subgroup Analysis for Precision Medicine.- Part III Precision Medicine in Clinic Trials and the applications to EHR Data.- Mining for Health: A Comparison of Word Embedding Methods for Analysis of EHRs Data.- Adaptive Designs for Precision Medicine in Clinical Trials: A Review and Some Innovative Designs.- Maximum Likelihood Estimation and Design and Inference Considerations for Sequential Multiple Assignment Randomized Trials.- Precision Medicine Designs for Cancer Clinical Trials.- Part IV Precision Medicine in Survival Analysis and Genomic Studies.- Variant Selection and Aggregation of Genetic Association Studies in Precision Medicine.- Leveraging Functional Annotations Improves Cross-population Genetic Risk Prediction.- A Soft-Thresholding Operator for Sparse Time-Varying Effects in  Survival Models.- Discovery of Gene-specific Time Effects on

Dr. Yichuan Zhao is a Professor of Statistics at Georgia State University in Atlanta. He has a joint appointment as associate member of the Neuroscience Institute, and he is also an affiliated faculty member of the School of Public Health at Georgia State University. His current research interest focuses on survival analysis, empirical likelihood methods, nonparametric statistics, analysis of ROC curves, bioinformatics, Monte Carlo methods, and statistical modelling of fuzzy systems. He has published more than 100 research articles in statistics and biostatistics, has co-edited six books on statistics, biostatistics and data science, and has been invited to deliver more than 200 research talks nationally and internationally. Dr. Zhao has organized the Workshop Series on Biostatistics and Bioinformatics since its initiation in 2012. He also organized the 25th ICSA Applied Statistics Symposium in Atlanta as the chair of the organizing committee to great success. In addition, the 6th ICSA China Conference that he organized as the chair of both the organizing committee and program committee was a huge success.  He is currently serving as associate editor, or on the editorial board, for several statistical journals. Dr. Zhao is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute.
Dr. Ding-Geng Chen is a fellow of the American Statistical Association and is currently the executive director and professor in biostatistics at the College of Health Solutions, Arizona State University. He is also an extraordinary professor and the SARChI in biostatistics at the University of Pretoria, an honorary professor at the University of KwaZulu-Natal, South Africa. Dr. Chen was a professor in Biostatistics at the University of North Carolina at Chapel Hill, a professor in biostatistics at the University of Rochester Medical School, and the Karl E. Peace Endowed Eminent Scholar Chair in Biostatistics at Georgia