Patent ID: 11875889
Assignee: KPN INNOVATIONS LLC
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A system for alimentary provisioning, the system comprising a computing device configured to:
record at least a biological extraction from a user;
generate an alimentary instruction set for the user including a plurality of target nutrient quantities, wherein generating the alimentary instruction set comprises:
training a first machine-learning model using first training data, wherein the first training data is represented in vector form and includes biological extraction data correlated with target nutrition quantity data;
inputting the at least a biological extraction to the trained first machine-learning model; and
outputting the alimentary instruction set from the trained machine-learning model as a function of the at least a biological extraction;

receive, from each alimentary provider device of a plurality of alimentary provider devices, a plurality of provider ingredients;
generate a plurality of ingredient combinations, wherein each ingredient combination is a combination of two or more provider ingredients of the plurality of provider ingredients; and
select a plurality of beneficial ingredient combinations for the user from the plurality of ingredient combinations, wherein selecting the plurality of ingredient combinations further comprises:
determining a nutrient listing corresponding to each ingredient combination of the plurality of ingredient combinations;
creating a distance metric from each nutrient listing to the alimentary instruction set, wherein creating the distance metric comprises:
representing each nutrient listing as a first vector;
representing the target nutrient quantities as a second vector; and
determining a quantitative value indicating a similarity between the first vector and the second vector, wherein the quantitative value includes a cosine similarity between the first vector and the second vector;

selecting at least an ingredient listing that minimizes the distance metric based on the cosine similarity between the first vector and the second vector; and
selecting the plurality of beneficial ingredient combinations as a function of the at least an ingredient listing that minimizes the distance metric.