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dc.contributor.advisorMagboo, Vincent Peter C.-
dc.contributor.authorMeren, Gil Troy P.-
dc.date.accessioned2015-07-25T17:24:43Z-
dc.date.available2015-07-25T17:24:43Z-
dc.date.issued2014-04-
dc.identifier.urihttp://cas.upm.edu.ph:8080/xmlui/handle/123456789/41-
dc.description.abstractIllnesses 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).en_US
dc.language.isoenen_US
dc.subjectbreast canceren_US
dc.subjectdata miningen_US
dc.subjectmedical recordsen_US
dc.subjectsurvival calculatoren_US
dc.subjectpredictive modelingen_US
dc.subjectSEERen_US
dc.titleBOSOM Calculator: A Breast Cancer Outcome - Survival Online Measurement Calculator using Data Mining and Predictive Modeling on SEER dataen_US
dc.typeThesisen_US
Appears in Collections:Computer Science SP

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