Invention Grant
- Patent Title: Systems and methods for predicting analyte concentrations via machine learning techniques
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Application No.: US17355157Application Date: 2021-06-22
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Publication No.: US11989629B2Publication Date: 2024-05-21
- Inventor: Nicole Leilani Ing , Glenn Clifford Forrester
- Applicant: Metre, Inc.
- Applicant Address: US CA Oakland
- Assignee: Metre, Inc.
- Current Assignee: Metre, Inc.
- Current Assignee Address: US CA Oakland
- Agency: Cognition IP, P.C.
- Agent Edward Steakley; Rajesh Fotedar
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G01N27/49 ; G01N33/497

Abstract:
Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to a Concentration Prediction Platform. According to various embodiments, the Concentration Prediction Platform receives an electrochemical signal and generates data based on deconvolving a respective contribution of an analyte(s) influencing the electrochemical signal. The Concentration Prediction Platform sends the data into one or more machine learning networks. The Concentration Prediction Platform receives, from the one or more machine learning networks, a predicted concentration of an analyte(s) influencing the electrochemical signal.
Public/Granted literature
- US20220114485A1 SYSTEMS AND METHODS FOR PREDICTING ANALYTE CONCENTRATIONS VIA MACHINE LEARNING TECHNIQUES Public/Granted day:2022-04-14
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