A goal of precision medicine1 is to stratify patients in order to improve diagnosis and medical treatment. Translational investigators are bringing to bear ever greater amounts of heterogeneous clinical data and scientific information to create classification strategies that enable the matching of intervention to underlying mechanisms of disease in subgroups of patients. Ontologies are systematic representations of knowledge that can be used to integrate and analyze large amounts of heterogeneous data, allowing precise classification of a patient. In this review, we describe ontologies and their use in computational reasoning to support precise classification of patients for diagnosis, care management, and translational research.
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