Individual cancer mortality prediction
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<subfield code="a">To improve cancer patients and survivors¿ access to life insurance, it is necessary to evaluate the mortality risk of a cancer patient on an individual basis. Mortality and survivorship prediction based on data can be used to supplement doctor opinion. Detailed information such as age, gender, race, age at diagnosis, cancer type, tumor size, histological information, and received treatment can be used to assess the risk of the patient or survivor. Predictive models can be calibrated to either experience data or doctors¿ estimate, with adjustments for future changes such as medical development.With more accurate underwriting and pricing for individual patients, it could lead to a higher acceptance rate of insurance applications from cancer patients and lower premium rates for applicants with low risk. This report explores cancer mortality term structure and its volatility using diagnostic, medical treatment and demographic information</subfield>
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