“Leveraging informatics-based approaches for clinical outcome prediction using electronic health record data”
Abstract: The delivery of precision medicine is predicated on the ability to link scientific knowledge with individual patient-level phenotypes in order to enable the identification of disease risk and/or the selection of optimal therapies. Using Neurofibromatosis Type 1 (NF1) as a model system, we focus on the driving hypothesis that machine learning techniques can be used to develop and validate predictive phenotypes applicable to risk stratification and disease management in NF1.
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