Machine learning for nutrient quantity estimation in score-based diets and methods of use thereof

Number of patents in Portfolio can not be more than 2000

United States of America Patent

PATENT NO 11803781
APP PUB NO 20230079862A1
SERIAL NO

17940798

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Abstract

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Systems and methods of the present disclosure use one or more processor(s) to receive a consumable preference and a daily score intake value associated with a user and to obtain a content data regarding consumable item including an amount of a first nutrient found in the consumable item. The processor(s) utilizes, in real-time, a nutrient prediction machine learning model to ingest the content data regarding the consumable item and predict an amount of a second nutrient in the consumable item based on the content data and a decision tree library of thousand nutrient decision trees. The processor(s) determines zero-scored consumable item based on the daily score intake value, the amount of the first nutrient, the amount of the second nutrient, and the consumable preference. The processor(s) instructs a computing device to utilize a graphical user interface element to identify the zero-scored consumable item on a screen of the computing device.

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Patent Owner(s)

  • WEIGHT WATCHERS INTERNATIONAL, INC.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Bünker, Judith Dulmen, DE 1 0
Daniel-Weiner, Reka New York, US 2 7
Foster, Gary Newtown Square, US 13 292
Gerwig, Ute Duesseldorf, DE 24 142
Skarlinski, Michael New York, US 1 0
Smith, Laura Bridgeport, US 17 265
Zaydel, Jacquelyn Jersey City, US 1 0

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