Welldoc, Inc (20250014760). SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS: Difference between revisions
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==Inventor(s)== | ==Inventor(s)== | ||
[[:Category:Anand K. Iyer of Potomac MD | [[:Category:Anand K. Iyer of Potomac MD US|Anand K. Iyer of Potomac MD US]][[Category:Anand K. Iyer of Potomac MD US]] | ||
[[:Category:Abhimanyu Kumbara of Columbia MD | [[:Category:Abhimanyu Kumbara of Columbia MD US|Abhimanyu Kumbara of Columbia MD US]][[Category:Abhimanyu Kumbara of Columbia MD US]] | ||
[[:Category:Mansur E. Shomali of Columbia MD | [[:Category:Mansur E. Shomali of Columbia MD US|Mansur E. Shomali of Columbia MD US]][[Category:Mansur E. Shomali of Columbia MD US]] | ||
[[:Category:Junjie Luo of Columbia MD | [[:Category:Junjie Luo of Columbia MD US|Junjie Luo of Columbia MD US]][[Category:Junjie Luo of Columbia MD US]] | ||
[[:Category:Guodong Gao of Clarksville MD | [[:Category:Guodong Gao of Clarksville MD US|Guodong Gao of Clarksville MD US]][[Category:Guodong Gao of Clarksville MD US]] | ||
==SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS== | ==SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS== | ||
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This abstract first appeared for US patent application 20250014760 titled 'SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS | This abstract first appeared for US patent application 20250014760 titled 'SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS | ||
==Original Abstract Submitted== | ==Original Abstract Submitted== | ||
Latest revision as of 08:53, 25 March 2025
SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS
Organization Name
Inventor(s)
Anand K. Iyer of Potomac MD US
Abhimanyu Kumbara of Columbia MD US
Mansur E. Shomali of Columbia MD US
Guodong Gao of Clarksville MD US
SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS
This abstract first appeared for US patent application 20250014760 titled 'SYSTEMS AND METHODS FOR CONTINUOUS GLUCOSE MONITORING OUTCOME PREDICTIONS
Original Abstract Submitted
methods and devices include predicting future glucose and engagement levels for a user by receiving the user's glucose levels collected by a continuous glucose monitoring (cgm) device over a time period, receiving engagement data associated with the user, wherein the engagement data are associated with the user's medication intake, diet, physical activity, laboratory results, and education activity, determining a first glycemia risk index (gri) value, determining, using a machine learning model and responsive to the user's glucose levels and the engagement data collected over the time period, one or more predictions for future glucose levels for the user including a prediction that a future gri value is greater than or less than the first gri value, and determining, using the machine learning model and responsive to the user's engagement data collected over the time period, one or more predictions for future engagement levels.
