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This project is about computational techniques applied to the practice of medicine, an information-based approach to a medical problem, and the ability to manage medical information in new ways. Using a set of computational tools, we demonstrate how computing allows medical professionals to manage and analyze data for families with inherited colorectal cancer syndromes and identify distinct clinical and genetic patterns suggestive of an inherited disease. Our aim is to predict the likelihood of a family member developing cancer, on the basis of family history, clinical criteria and genetic data. Toward this end, we have developed a medical knowledge acquisition tool for clinicians that integrates clinical, genetic and pedigree data that has demonstrated its effectiveness as a diagnostic and therapeutic platform. This system serves as a platform for analytical and data mining methods that can reason over available phenotypic and genome-scale measurements to provide a better understanding of hereditary colorectal cancer. The importance of the framework is illustrated in the context of solving a complex classification problem through a collaborative effort of colorectal surgeons and biologists. |
