Abstract:
Illnesses of high mortality rate such as breast cancer elicit questions related to
the patient’s time left to live. The common methods used to arrive at an estimate
include comparing the patient’s health condition to previous medical records and
treatments, referral to statistically-computed survival rates based from historical
records, or consulting another breast cancer expert.
The application of data mining on medical records to create predictive models
for cancer survivability has been proven to hold significant accuracy by numerous
scientific and applied researches throughout the years. Agrawal et al.’s “Lung
Cancer Outcome Calculator” provides a framework for developing a predicted
survival calculator for different cancers based on a patient’s health condition.
This research aims to develop the Breast Cancer Outcome - Survival Online
Measurement Calculator (BOSOM Calculator), an online application that takes a
patient’s clinical cancer data to give a predicted cancer survival based on a dataset
from the Surveillance, Epidemiology, and End Results Program (SEER).