Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data

4 Apr 2018Andrew L. BeamBenjamin KompaAllen SchmaltzInbar FriedGriffin WeberNathan P. PalmerXu ShiTianxi CaiIsaac S. Kohane

Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this article, we present a new set of embeddings for medical concepts learned using an extremely large collection of multimodal medical data... (read more)

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