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

Claim 0:
1. An apparatus for assigning a phenotype cluster to a user, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to:
receive user data from a user;
generate a cluster machine learning model;
classify 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;

assign the classified user data 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 trained conicity index machine learning model;
generate alimentary data as a function of the one or more cohort labels; and
output 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.