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The motivation to develop this research work is based on: Nowadays there are not knowledge models for all the medical activities that can be induced from medical data, there are not inductive learning solutions for all the medical activities, and there is not an integral model that formalizes the concept of medical procedure. Therefore, our main objective is to develop a computable model based in knowledge that integrates all the decision and planning activities for the medical diagnosis, treatment and prognosis. To achieve this main objective: first, we explain the research problem. Second, we describe the background of the work from both the medical and the informatics contexts. Third, we explain the development of the research proposal based on four main contributions: a novel knowledge representation model and inductive learning methodology, based in data, to the planning activity in medical diagnosis and treatment; a novel inductive learning methodology to the decision activity in medical prognosis, and finally, a novel computable model, based on data and knowledge, which integrates the decision and planning activities of medical Diagnosis, Treatment and Prognosis.
About the author
John A. Bohada is Software Ph.D (UPC-Barcelona, Spain), Magister on Computer Science (UNAB-Bucaramanga, Colombia). Actually, he works as dean of the Faculty of Engineering and director of the MUISCA research group (Fundacin Universitaria Juan de Castellanos, Colombia).
