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This project has the purpose of exploring the use of existing AI methods and machine learning algorithms for health data assessment in order to develop build a recommender system. The primary goal is to plan, develop and test a knowledge-base of health recommendations to be used for automation, increased health and performance. Our methodology for building the Diagnostics and recommender (D-R) system is sub-divided into three steps: building a model for analyzing the structured data, building a model for extrapolating the unstructured data and then finally a model that correlates them to produce an appropriate recommendation.
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