17143083. GENERATING EMBEDDINGS OF MEDICAL ENCOUNTER FEATURES USING SELF-ATTENTION NEURAL NETWORKS (Google LLC)
GENERATING EMBEDDINGS OF MEDICAL ENCOUNTER FEATURES USING SELF-ATTENTION NEURAL NETWORKS
Organization Name
Inventor(s)
Andrew M. Dai of San Francisco CA US
Gerardo Flores of Berkeley CA US
Michael Ward Dusenberry of San Mateo CA US
Zhen Xu of Mountain View CA US
GENERATING EMBEDDINGS OF MEDICAL ENCOUNTER FEATURES USING SELF-ATTENTION NEURAL NETWORKS
This abstract first appeared for US patent application 17143083 titled 'GENERATING EMBEDDINGS OF MEDICAL ENCOUNTER FEATURES USING SELF-ATTENTION NEURAL NETWORKS
Original Abstract Submitted
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing data about a medical encounter using neural networks. One of the methods includes obtaining features for a medical encounter associated with the patient, each feature representing a corresponding health event associated with the medical encounter and each of the plurality of features belonging to a vocabulary of possible features that each represent a different health event; and generating respective final embeddings for each of the features for the medical encounter by applying a sequence of one or more self-attention blocks to the features for the medical encounter, wherein each of the one or more self-attention blocks receives a respective block input for each of the features and applies self-attention over the block inputs to generate a respective block output for each of the features.
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