AI RESEARCH
Forecasting Oncology Demand Trends with Boosting-Based Bayesian Conjugate Models
arXiv CS.LG
•
ArXi:2605.05270v1 Announce Type: cross Accurate trend forecasting in healthcare time series is essential for planning and resource allocation. This paper proposes a Bayesian framework for predicting oncology demand trends, modeling weekly appointments as a Poisson process with a Gamma prior to the demand rate. To enhance adaptability and capture persistent directional patterns, we incorporate a residual-based boosting mechanism grounded in a Gamma-Log-Normal conjugate structure.