Abstract: A system and method are provided for controlling a plurality of fuel cells. The method includes coordinating a distribution of a power demand in response to a power request of a power system comprising a plurality of fuel cells, the power output of each of the fuel cells selected based on a respective efficiency of each of the fuel cells.

Abstract: A suite of fluidless predictive machine learning models includes a fluidless mortality module, smoking propensity model, and prescription fills model. The fluidless machine learning models are trained against a corpus of historical underwriting applications of a sponsoring enterprise, including clinical data of historical applicants. Fluidless models are trained by application of a random forest ensemble including survival, regression, and classification models. The trained models produce high-resolution, individual mortality scores. A fluidless underwriting protocol runs these predictive models to assess mortality risk and other risk attributes of a fluidless application that excludes clinical data to determine whether to present an accelerated underwriting offer.