Kpn Innovations, Llc.

Other

Kenneth Neumann

An apparatus for resource guidance, wherein the apparatus comprises at least a processor; and a memory communicatively connected to the at least a processor, wherein the memory containing instructions configuring the at least a processor to receive a request for a resource containing a desired allocation; identify a first nourishment provider for a first resource; label the first resource as a function of the desired allocation; identify a second nourishment provider for a second resource; label the second resource as a function of the first nourishment resource and the desired allocation; receive a depot label from the first nourishment provider and the second nourishment provider; aggregate the first resource and the second resource as a function of the depot label; and generate resource guidance using the depot label.

Apparatus and method for resource guidance

A system for determining a prescriptive therapy instruction set may include a computing device configured to receive a first subject prescription datum associated with a first subject; receive a first subject tolerance datum associated with the first subject; determine a prescriptive therapy instruction set by training a prescriptive therapy instruction set machine learning model on a training dataset including a plurality of example subject prescription data and subject tolerance data as inputs correlated to a plurality of example prescriptive therapy instruction sets as outputs; and generating the prescriptive therapy instruction set as a function of the subject prescription datum and the subject tolerance datum using the trained prescriptive therapy instruction set machine learning model; receive a second subject tolerance datum associated with the first subject; and retrain the prescriptive therapy instruction set machine learning model as a function of the second subject tolerance datum.

Methods and systems for determining a prescriptive therapy instruction set

A system for providing alimentary combinations in a packet-based graphical user interface generated using distance metrics is disclosed. The system includes a computing device designed and configured to receive user classification data, wherein the user classification training data includes a plurality of elements correlating user data entries to user set identifiers. The computing device is configured to receive at least an element of user data, train a user classifier as a function of the user classification training data using a machine learning algorithm. The computing device is configured to classify the at least an element of user data to a user set identifier, set a non-alimentary ordering criterion default parameter as a function of the user set identifier, and order an alimentary combination as a function of the non-alimentary ordering criterion. A method of providing alimentary combinations in a packet-based graphical user interface generated using distance metrics is also disclosed.

Methods and systems for providing alimentary combinations in a packet-based graphical user interface generated using distance metrics

A system for causative chaining of prognostic label classifications includes a classification device configured to receive training data including a plurality of first data entries, each including at least a first element of physiological state data and at least a correlated first prognostic label and a plurality of second data entries, each including at least a second prognostic label and at least a correlated third prognostic label, and to record at least a first biological extraction. The system includes a prognostic label learner configured to generate at least a first prognostic output as a function of the first training set and the at least a physiological test sample, and a causal link learner configured to generate at least a second prognostic output causally linked to the first prognostic output as a function of the second training set and the at least a first prognostic output.

Methods and systems for causative chaining of prognostic label classifications

A system for generating a dental nourishment program includes a computing device configured to receive at least a dental factor, retrieve, a dental parameter, generate, using the dental parameter, an alimentary model, wherein the alimentary model includes determining a respective effect of each alimentary level of a plurality of alimentary levels on the dental parameter, generating the alimentary model as a function of the respective effect, identify, using the alimentary model, a plurality of alimentary elements, develop, using plurality of alimentary elements, a hygienic model, wherein the hygienic model includes determining, a plurality of hygienic patterns relating dental hygiene in relation to consumption of the plurality of alimentary elements, developing the hygienic model as a function of the hygienic patterns and the plurality of alimentary elements, and build a dental nourishment program using the hygienic model and the nutritional model.

Systems and methods for generating a dental nourishment program

In an aspect, an apparatus for scoring a nutrient is presented. An apparatus may include at least a processor and a memory communicatively connected to the at least a processor. A memory contains instructions configuring at least a processor to receive user data from a user. At least a processor classifies a user to a profile cluster as a function of user data. At least a processor assigns the user one or more cohort labels as a function of the user data. At least a processor receives edible data. At least a processor extracts, from edible data, at least a nutrient. At least a processor scores at least a nutrient as a function of a profile cluster of a user.

Apparatus and method for scoring a nutrient

A system for confirming an advisory interaction with an artificial intelligence platform. The system includes a constitutional generator module configured to receive a first advisory input, retrieve an expert input, select a machine-learning process as a function of the expert input, and generate a therapeutic corrector. The system includes a constitutional advisory module configured to display a therapeutic corrector on a graphical user interface and receive a second advisory input. The system includes a best practices module the best practices module designed and configured to retrieve from an expert database a best practices training set, calculate an optimal vector output, generate an optimal vector output containing an expected therapeutic corrector implementation response, authenticate a second advisory input, and update the best practices module.

Methods and systems for confirming an advisory interaction with an artificial intelligence platform

A system for generating a cancer alleviation nourishment plan includes a computing device configured to receive at least a cancer biomarker, retrieve a cancer profile, identify, using the cancer profile, a plurality of nutrition elements, including assigning the cancer profile to a cancer category, wherein the cancer category summarizes the current malignancy state of the user, calculating, according to the cancer category, a plurality of nutrient amounts, wherein calculating the plurality of nutrient amounts includes determining an effect on the cancer profile and calculating the plurality of nutrient amounts as a function of the effect, wherein the plurality of nutrient amounts is intended to result in cancer prevention, identifying, as a function of the plurality of nutrient amounts, the plurality of nutrition elements, wherein the plurality of nutrition elements contain the plurality of nutrient amounts, and generate, using the plurality of nutrition elements, the cancer prevention nourishment plan.

Systems and methods for generating a cancer alleviation nourishment plan

An apparatus for generating cryptographic keys associated with a biological extraction is disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive a plurality of biological extractions from a plurality of users. The memory instructs the processor to classify each of the plurality of biological extractions to a plurality of biological extraction clusters. The memory instructs the processor to generate an interconnection metric as a function of a comparison between the plurality of biological extraction clusters. The memory instructions the processor to generate an interconnection metric as a function of a comparison between the plurality of biological extraction clusters using a metric machine learning model. The memory instructs the processor to generate a cluster key associated with the interconnection metric and a biological extraction cluster of the plurality of biological extraction clusters.

Method and system for generating cryptographic keys associated with biological extraction data

An artificial intelligence system for analyzing imagery, the system comprising a computing device, the computing device designed and configured to receive a plurality of photographs related to a human subject; analyze the plurality of photographs to identify a conditional indicator contained within the plurality of photographs; generate a classification algorithm utilizing the conditional indicator, wherein the classification algorithm utilizes the conditional indicator as an input and outputs a conditional profile; and determine a conditional status of the human subject utilizing the conditional profile.

Artificial intelligence methods and systems for analyzing imagery

A system for arranging and displaying guided recommendations using a graphical user interface based on biological extraction, the system comprising a computing device configured to receive, from a wearable device located at a user, biological extraction data and at least a datum of user activity data, classify the biological extraction and the at least a datum of user activity as a function of at least a datum of a user fingerprint, select at least a compatible element as a function of the training data and the user fingerprint, wherein the compatible element comprises a guided recommendation, and generate a representation using a graphical user interface of the compatible element.

Methods and systems for arranging and displaying guided recommendations via a graphical user interface based on biological extraction

A system for generating a cancer alleviation nourishment plan including a computing device configured to receive at least a cancer biomarker relating to a user, where the cancer biomarker indicates the presence of cancer, retrieve a cancer profile related to the user, assign the cancer profile to a cancer category, wherein the cancer category includes a determination of a type of tumor, identify, using the cancer profile, a plurality of nutrition elements for the user, identifying, as a function of the plurality of nutrient amounts, the plurality of nutrition elements for cancer alleviation, and generate, using the plurality of nutrition elements, a cancer alleviation nourishment plan. A method for generating a cancer alleviation nourishment plan is also disclosed.

An apparatus and method for optimizing nutrition and health, comprising at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to receive at least a biological extraction from a user, receive a discovery center experience score related to a user, retrieve a plurality of nutrient labels describing a plurality of nutrients, determine, as a function of the discovery center experience score and biological extraction, an importance factor of a nutrient of a plurality of nutrients and display the importance factor of a nutrient of a plurality of nutrients to a user.

Methods and systems for generating a vibrant compatibility plan using artificial intelligence

The present disclosure is generally directed to an apparatus for using a feedback loop to optimize meals, may include at least a processor; and a memory communicatively connected to the processor, the memory containing instructions configuring the at least a processor to retrieve nutrition data from a database. The processor may be configured to generate an optimization score, wherein generating the optimization score may include training an optimization machine-learning model, wherein the optimization machine-learning model is trained with optimization training data, inputting a nutrient quantity to the optimization machine-learning model to output a target nutrient score, and generating an optimization score as a function of the nutrition data and the target nutrient score.

Apparatus and method for using a feedback loop to optimize meals

A system for optimizing supplement decisions is disclosed. The system includes a computing device configured to receive a longevity inquiry from a remote device. The system retrieves a biological extraction pertaining to a user and identifies a longevity element associated with a user. The system selects an ADME model utilizing a biological extraction. The system generates a machine-learning algorithm utilizing the selected ADME model to input a longevity element associated with a user as an input and output an ADME factor. The system identifies a second longevity element compatible with the ADME factor as a function of the first longevity element. The system selects the second longevity element as a tolerant longevity element. A method for optimizing supplement decisions is also disclosed.

Growing community of inventors

Lakewood, CO, United States of America

Kenneth Neumann