Machine learning for nutrient quantity estimation in score-based diets and methods of use thereof
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United States of America Patent
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Oct 31, 2023
Grant Date -
Mar 16, 2023
app pub date -
Sep 8, 2022
filing date -
Sep 8, 2021
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Abstract
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.
International Classification(s)
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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