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AI Biotech/Diagnostics: Cardio
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Application US20200077931
Published 2020-03-12
Forecasting Blood Glucose Concentration
A method, a system and a computer program product for forecasting blood glucose concentration. One or more features for training a blood glucose concentration forecasting model are determined. The features are determined based on one or more input data parameters associated with a user in a plurality of users. Using the determined one or more features, the blood glucose concentration forecasting model is trained. Using the trained blood glucose concentration forecasting model, one or more expected blood glucose concentrations for the user are generated.
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- 1. A computer-implemented method, comprising:
determining one or more features for training a blood glucose concentration forecasting model, wherein the one or more features are determined based on one or more input data parameters associated with a user in a plurality of users; training, using the determined one or more features, the blood glucose concentration forecasting model; and generating, using the trained blood glucose concentration forecasting model, one or more expected blood glucose concentrations for the user.
- 11. A system comprising:
at least one programmable processor; and a non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
determining one or more features for training a blood glucose concentration forecasting model, wherein the one or more features are determined based on one or more input data parameters associated with a user in a plurality of users;
training, using the determined one or more features, the blood glucose concentration forecasting model; and
generating, using the trained blood glucose concentration forecasting model, one or more expected blood glucose concentrations for the user.
- 21. A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
determining one or more features for training a blood glucose concentration forecasting model, wherein the one or more features are determined based on one or more input data parameters associated with a user in a plurality of users; training, using the determined one or more features, the blood glucose concentration forecasting model; and generating, using the trained blood glucose concentration forecasting model, one or more expected blood glucose concentrations for the user.
