3 papers
cs.CR2026
Privacy-Preserving Cohort Analytics for Personalized Health Platforms: A Differentially Private Framework with Stochastic Risk Modeling
Richik Chakraborty, Lawrence Liu, Syed Hasnain
Personalized health analytics increasingly rely on population benchmarks to provide contextual insights such as ''How do I compare to others like me?'' However, cohort-based aggreg…
stat.ME2026
Progressive Bayesian Confidence Architectures for Cold-Start Personal Health Analytics: Formalizing Early Insight Through Posterior Contraction and Risk-Aware Interpretation
Richik Chakraborty
Personal health analytics systems face a persistent cold-start dilemma: users expect meaningful insights early in data collection, while conventional statistical inference requires…
stat.ME2026
Beyond P-Values: Importing Quantitative Finance's Risk and Regret Metrics for AI in Learning Health Systems
Richik Chakraborty
The increasing deployment of artificial intelligence (AI) in clinical settings challenges foundational assumptions underlying traditional frameworks of medical evidence. Classical…