Predicting Colorectal Cancer Mortality: Models to Facilitate Patient-Physician Conversations and Inform Operational Decision Making

被引:9
作者
Bjarnadottir, Margret [1 ]
Anderson, David [2 ]
Zia, Leila [3 ]
Rhoads, Kim [4 ]
机构
[1] Univ Maryland, RH Smith Sch Business, College Pk, MD 20742 USA
[2] CUNY, Baruch Coll, Zicklin Sch Business, New York, NY 10010 USA
[3] Wikimedia Fdn, San Francisco, CA 94108 USA
[4] Stanford Univ, Sch Med, Stanford, CA 94305 USA
关键词
data mining; medical decision-making; survival analysis; personalized medicine; CARE; SURVIVAL; LIFE; CHEMOTHERAPY; END; PERFORMANCE; QUALITY; COMMUNICATION; DISPARITIES; TECHNOLOGY;
D O I
10.1111/poms.12896
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:2162 / 2183
页数:22
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