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Personalized Medicine: Development of a Predictive Computational Model for Personalized Therapeutic Interventions

dc.contributor.authorKureshi, Nelofar
dc.contributor.copyright-releaseNot Applicableen_US
dc.contributor.degreeMaster of Health Informaticsen_US
dc.contributor.departmentHealth Informaticsen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.external-examinern/aen_US
dc.contributor.graduate-coordinatorn/aen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.thesis-readerDr. Samina Abidien_US
dc.contributor.thesis-readerDr. Denis Riordanen_US
dc.contributor.thesis-supervisorDr. Syed Sibte Raza Abidi, Dr. Christian Blouinen_US
dc.date.accessioned2013-08-19T16:20:40Z
dc.date.available2013-08-19T16:20:40Z
dc.date.defence2013-08-02
dc.date.issued2013-08-19
dc.description.abstractLung cancer is the leading cause of cancer-related deaths among men and women. Non-Small Cell Lung Cancer (NSCLC) constitutes the most common type of lung cancer and is frequently diagnosed at advanced stages. In the past decade, discovery of Epidermal Growth Factor Receptor (EGFR) mutations have heralded a new paradigm of personalized treatment for NSCLC. Clinical studies have shown that molecular targeted therapies increase survival and improve quality of life in patients. Despite these advances, the realization of personalized therapies for NSCLC faces a number of challenges including the integration of clinical and genetic data and a lack of clinical decision support tools to assist physicians with patient selection. This thesis demonstrates the development of a predictive computational model for personalized therapeutic interventions in advanced NSCLC. The findings suggest that the combination of clinical and genetic data significantly improves the model’s predictive performance for tumor response than clinical data alone.en_US
dc.identifier.urihttp://hdl.handle.net/10222/35383
dc.language.isoenen_US
dc.subjectPersonalized medicine, Non-small cell lung cancer, Epidermal growth factor receptor, Decision supporten_US
dc.titlePersonalized Medicine: Development of a Predictive Computational Model for Personalized Therapeutic Interventionsen_US

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