Cerner Innovation, Inc.

Maulik Gandhi

Christopher S Finn

Uttam Ramamurthy

James Gritter

David Dellsperger

Stephen Patel

Adam Sabaliauskas

Brandon Davis

Particular embodiments can update a deployed machine learning model with actual entity data depending on anomalies detected in stream data, which can be stored to a computer object, such as a journal. Various embodiments map particular subsets of a larger pool of raw input data to the particular models that need the input data and store the raw input data to computer objects so that the corresponding machine learning models can make predictions according to any suitable policy or triggering event on any of the data located in the computer objects. Such mapping allows each machine learning model to continuously make predictions based on the data it needs.

Intelligent updating and data processing for deployed machine learning models

Growing community of inventors

De Pere, WA, United States of America

Maulik Gandhi