Predicting Colorectal Cancer Mortality: Models to Facilitate Patient-Physician Conversations and Inform Operational Decision Making
Margret Bjarnadottir, David Anderson, Leila Zia, Kim Rhoads
Production and Operations Management · 2018 · Volume 27 · Issue 12
Abstract
Having accurate, unbiased prognosis information can help patients and providers make better decisions about what course of treatment to take. Using a comprehensive dataset of all colorectal cancer patients in California, we generate predictive models that estimate short-term and medium-term survival probabilities for patients based on their clinical and demographic information. Our study addresses some of the contradictions in the literature about survival rates and significantly improves predictive power over the performance of any model in previously published studies.
Keywords
data mining, medical decision-making, survival analysis, personalized medicine
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