Patent ID: 11862324
Assignee: KPN INNOVATIONS LLC
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 10:
11. A method for outputting an alimentary program to a user, the method comprising:
receiving, by a processor, user data from a user;
generating, by the processor, a cluster machine learning model;
classifying, by the processor, the user data to one or more phenotypic clusters as a function of the user data using the cluster machine learning model, wherein classifying the user data to one or more phenotypic clusters comprises:
classifying the user data to an energy band using an energy band machine learning model trained using energy band training data, wherein the energy band training data comprises a plurality of historic phenotypic data as input correlated to a plurality of historic energy bands as output;
classifying the user data to a micronutrient band using a micronutrient band machine learning model trained using micronutrient band training data, wherein the micronutrient band training data comprises a plurality of historic phenotypic data as input correlated to a plurality of historic micronutrient bands as output;
classifying the user data to a conicity index using a conicity index machine learning model trained using conicity index training data, wherein the conicity index training data comprises a plurality of historic phenotypic data as input correlated to a plurality of historic conicity index as output;
training the cluster machine learning model using cluster training data, wherein the cluster training data comprises a plurality of energy bands, conicity indices, and micronutrient bands as input correlated to a plurality of phenotypic clusters as output; and
classifying the user data to the one or more phenotypic clusters as a function of the energy band, the micronutrient band, and the conicity index using the cluster machine learning model;

assigning, by the processor, the classified user data to one or more cohort labels as a function of the one or more phenotypic clusters, wherein at least a cohort label is associated with the conicity index generated using the conicity index machine learning model;
generating, by the processor, alimentary data as a function of the one or more cohort labels; and
outputting, by the processor, an alimentary program to the user as a function of the alimentary data, wherein the alimentary program comprises an ingredient combination and one or more preparation instructions of the ingredient combination.