Google Inc.

Biocogniv Inc.

Artur Borges Adib

Konstantin V Mandrika

Hemal Shah

Tali Jill Sason

Matthew Ryan Willis

Robert A Levine

Tanya S Kanigan

Steven Andrew Wallace

Methods, systems, and apparatus, including computer programs encoded on computer storage media for dynamic model selection and rule based data interpretation. The system receives a plurality of data sets from one or more external computing systems, each of the data sets including multiple data fields including one or more code values and data values for one or more medical tests. The system provides a plurality of medical test processing models wherein each medical test processing model includes a data interpretation rule structure for processing different types of the medical tests. The system selects a particular medical test processing model based on the one or more code values of the medical test. The system uses the selected medical test processing model to process the data values of the one or more medical tests to generate an interpreted medical test data set.

Dynamic model selection and rule based data interpretation

A method of determining the risk of developing a known disease or condition or of identifying the presence of the known disease or condition in a subject includes obtaining subject data that includes results of blood tests. The blood tests include a basic metabolic panel (BMP) and a complete blood count (CBC) panel. The method further includes classifying the subject data with respect to the risk of the subject having or developing the known disease or condition by using the subject data in a machine learning classification system. The classification system includes a machine learning model previously trained on BMP and CBC data from a positive group of training subjects who received a diagnosis of the disease or condition and from a negative group of training subjects who were not diagnosed to have the disease or condition.

Method of early detection, risk stratification, and outcomes prediction of a medical disease or condition with machine learning and routinely taken patient data

A software plugin integrated with the development environment maintains a list of independently managed assets that are installed within the development environment. The independently managed assets are provided by an entity with which the software plugin can communicate to determine whether newer versions of the assets have been released. The software plugin automatically downloads and installs the newer version of the assets with minimal, if any, user intervention. Further, the software plugin monitors the interdependencies between different assets installed within the development environment. When updating to a newer version of an asset, the software plugin identifies any conflicts that may occur with regards to the interdependencies when the asset is updated.

Managing software assets installed in an integrated development environment

Growing community of inventors

South Burlington, VT, United States of America

Artur Borges Adib