Invention Application
- Patent Title: AUTOMATED MACHINE LEARNING MODEL FEEDBACK WITH DATA CAPTURE AND SYNTHETIC DATA GENERATION
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Application No.: US17235026Application Date: 2021-04-20
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Publication No.: US20220335328A1Publication Date: 2022-10-20
- Inventor: Travis R. Frosch , Anastasia Marie Van Dyke Dunn , Garry M. Whitley , Alvaro Molina , Weston R. Olmstead
- Applicant: GE Precision Healthcare LLC
- Applicant Address: US WI Milwaukee
- Assignee: GE Precision Healthcare LLC
- Current Assignee: GE Precision Healthcare LLC
- Current Assignee Address: US WI Milwaukee
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N5/04 ; G16H50/20 ; G16H30/20

Abstract:
Systems and techniques that facilitate automated machine learning model feedback with data capture and synthetic data generation are provided. In various embodiments, a receiver component can receive electronic input identifying a deployed machine learning model. In various aspects, a listener component can retrieve from a data pipeline a data candidate that has been analyzed by the deployed machine learning model, an inference generated by the deployed machine learning model based on the data candidate, and an expert conclusion provided by a subject matter expert based on the data candidate. In various instances, a comparison component can compare the inference with the expert conclusion to determine whether the inference is consistent with the expert conclusion. In various cases, an augmentation component can, in response to a determination that the inference is not consistent with the expert conclusion, generate a set of synthetic training data based on the data candidate.
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