Modeling Recovery Curves With Application to Prostatectomy
2015-04-27Code Available0· sign in to hype
Fulton Wang, Tyler H. McCormick, Cynthia Rudin, John Gore
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Abstract
We propose a Bayesian model that predicts recovery curves based on information available before the disruptive event. A recovery curve of interest is the quantified sexual function of prostate cancer patients after prostatectomy surgery. We illustrate the utility of our model as a pre-treatment medical decision aid, producing personalized predictions that are both interpretable and accurate. We uncover covariate relationships that agree with and supplement that in existing medical literature.