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US 2026/0272379 A1Published application
Systems, methods, and apparatuses for continuous monitoring and effective management of hydration
OwnerShovito Barua Soumma, Asiful Arefeen +2inventors
InventorsShovito Barua Soumma, Asiful Arefeen, Stavros Kavouras, Hassan Zadeh
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Abstract
A real time automated hydration management solution is described herein that uses predictive and counterfactual generation models to recommend optimal behavior for normalizing hydration levels based on data collected in real time.
Claims17
A method comprising,
- receiving a feature vector for a plurality of subjects, wherein a feature vector comprises feature data elements of a subject;
- applying a predictive model to the feature vector of the plurality of subjects, wherein the predictive model classifies the plurality of subjects as hydrated or dehydrated;
- identifying at least one subject of the plurality of subjects that is classified as dehydrated;
- generating candidate counterfactual feature vectors for the at least one subject, wherein the generating the candidate counter factual feature vectors comprises identifying counterfactual changes to the feature data elements which transition the predictive model classification of the subject from dehydrated to hydrated, where the candidate counter factual feature vectors comprise only identified counterfactual feature data elements;
- computing a diversity distance between each possible pairing of candidate counter factual feature vectors;
- generating a preference aware cost for the candidate counterfactual vectors;
- generating an optimization score for each candidate counter factual feature vector using a weighted sum of the diversity score and the preference aware cost for each pair;
- applying a greedy selection process to select a subset of the counterfactual feature vectors;
- and
- providing the subset of the counterfactual feature vectors to the subject.
7 more elements
A system comprising,
- one or more applications running on at least one processor of a remote server, the one or more applications communicatively coupled with a mobile device application running on a processor of a mobile device, the one or more applications configured to:
- receive a feature vector for a plurality of subjects, wherein a feature vector comprises feature data elements of a subject;
- apply a predictive model to the feature vector of the plurality of subjects, wherein the predictive model classifies the plurality of subjects as hydrated or dehydrated;
- identify at least one subject of the plurality of subjects that is classified as dehydrated;
- generate candidate counterfactual feature vectors for the at least one subject, wherein the generating the candidate counter factual feature vectors comprises identifying counterfactual changes to the feature data elements which transition the predictive model classification of the subject from dehydrated to hydrated, where the candidate counter factual feature vectors comprise only identified counterfactual feature data elements;
- compute a diversity distance between each possible pairing of candidate counter factual feature vectors;
- generate a preference aware cost for the candidate counterfactual vectors;
- generate an optimization score for each candidate counter factual feature vector using a weighted sum of the diversity score and the preference aware cost for each pair;
- and
- apply a greedy selection process to select a subset of the counterfactual feature vectors;
- provide the subset of the counterfactual feature vectors to the one or more applications for display to a user.
8 more elements
Dependencies are inferred from the claim text.