Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine learning. One of the methods includes receiving a message; parsing the message to identify individual sentences within the message; encoding each sentence into a vector that represents a semantic meaning of the sentence; applying one or more classification models to the message including: providing each vector to a machine learning model, wherein the machine learning model is trained to generate a prediction of one or more classifications for each sentence of the message; generating a predicted classification for the message as a whole; and determining a message routing based on the predicted classification.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for machine learning. One of the methods includes receiving a message including an attachment document; determining one or more first features from content of the attachment document; providing the first features to one or more classification models, the one or more classification models including a machine learning model, wherein the machine learning model is trained to generate a prediction of one or more classifications of attachment documents based on input features; generating one or more predicted classifications of the attachment document; and associating the one or more predicted classifications with the attachment document.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for natural language processing. One of the methods includes the steps of receiving a first set of labeled data from a first data source; receiving a text string from a second data source; performing natural language processing on the text string to extract particular text portions and generate a second set of labeled data; performing a comparison between the first set of labeled data and the second set of labeled data; and generating an output based on the comparison.

Abstract: Systems, methods, and articles of manufacture for monitoring and assessing health record data quality are disclosed. The system monitors and assesses health record data quality in an on-boarding environment and/or a production environment. The system ingests health record data transmitted by various health record data sources. The system monitors the ingestion of health record data to detect data quality errors occurring during the ingestion. Based on the data quality errors, and in response to detecting one or more data quality errors, the system generates a data quality score that can be used to determine the overall quality of data being ingested into the system.