Kpn Innovations, Llc.

Other

Kenneth Neumann

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.

Systems and methods for generating a cancer alleviation nourishment plan

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.

Methods and systems for optimizing supplement decisions

An apparatus for physiologically informed gestational inquiries is disclosed. The apparatus includes at least a processor and memory communicatively connected to the at least a processor. The memory instructs the processor to receive a biological extraction from the user. The memory instructs the processor to receive a gestational inquiry from the user. The memory instructs the processor to separate the gestational inquiry from a description of the gestational inquiry. The memory instructs the processor to determine a gestational target as a function of the gestational inquiry and the biological extraction. The memory instructs the processor to generate a gestational report as a function of the gestational target.

Methods and systems for physiologically informed gestational inquiries

A system for predicting alimentary element ordering based on biological extraction includes a computing device configured to identify an alimentary profile, wherein identifying further comprises obtaining a biological extraction of a user, determining an alimentary element order chronicle of a user, and identifying the alimentary profile as a function of the biological extraction and the alimentary element order chronicle, determine an edible of interest, wherein determining the edible further comprises receiving a datum as a function of an edible database, and determining the edible of interest as a function of the alimentary profile and the datum, obtain a nourishment information associated to the edible of interest, and generate a nourishment score as a function of the edible of interest and the nourishment information.

Method for and system for predicting alimentary element ordering based on biological extraction

A system for generating a gestational disorder nourishment program comprising a computing device, the computing device configured to obtain a maternal marker, calculate a gestational phase as a function of the maternal marker, wherein calculating the gestational phase further comprises, identifying a gestational goal, and calculating the gestational phase as a function of the maternal marker and the gestational goal as a function of a gestational machine-learning model, determine an edible as a function of the gestational phase, and generate a nourishment program as a function of the edible.

System and method for generating a gestational disorder nourishment program

In an aspect, a system for generating lifestyle change recommendations based on biological extractions includes a computing device designed and configured for receiving a biological extraction pertaining to a user generating, using a first machine-learning process, a plurality of lifestyle intervention combinations as a function of the biological extraction, assigning, to each lifestyle intervention combination of the plurality of lifestyle intervention combinations, a degree of projected user adherence to the lifestyle intervention combination, wherein assigning further comprises performing a second machine learning process, and selecting, from the plurality of lifestyle intervention combinations, a lifestyle intervention combination as a function of the degree of projected user adherence of the selected lifestyle intervention combination.

Methods and systems for generating lifestyle change recommendations based on biological extractions

A system for generating a nourishment program includes a computing device configured to retrieve a nociception parameter, classify the nociception parameter to a nociception grouping, identify, using the nociception grouping, a plurality of nutrition elements, wherein identifying the plurality of nutrition elements includes generating a plurality of nutritional metrics associated with reduction of nociception as a function of the nociception grouping, determining a respective effect of each nutritional metric of the plurality of nutritional metrics on the nociception parameter, calculating at least a nutritional level as a function of the respective effect of each nutritional metric, wherein the at least a nutritional level comprises an amount intended to address the nociception parameter, and identifying the plurality of nutrition elements as a function of the at least a nutritional level, and generate a nociception nourishment program using the plurality of nutrition elements.

Systems and methods for generating a nociception nourishement program

A system for generating a geographically linked nourishment program comprising a computing device configured to obtain a biochemical element, identify a vigor panel as a function of the biochemical element, wherein identifying further comprises receiving a geographical indicator, ascertaining a geographical predictive element as a function of the geographical indicator, and identifying the vigor panel as a function of the geographical predictive element and the biochemical element using a geographical machine-learning model, determine an edible as a function of the vigor panel, and generate a nourishment program as a function of the edible.

System and method for generating a geographically linked nourishment program

A system for generating a lifestyle-based disease prevention plan, the system including a computing device configured to receive at least a user biomarker input, produce a user profile as a function of the at least a user biomarker input, and generate a lifestyle-based disease prevention plan as a function of the user profile including training a machine learning process with a lifestyle training data set where the lifestyle training data set further comprises lifestyle elements correlated to a plurality of outputs containing diseases prevented and producing the lifestyle-based disease prevention plan as a function of the user profile and machine learning process.

Systems and methods for generating a lifestyle-based disease prevention plan

In an aspect, an apparatus for generating an ingredient chain is presented. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. A memory contains instructions configuring at least a processor receive recipe data from a user. At least a processor is configured to extract a plurality of ingredients from recipe data. At least a processor is configured to classify, utilizing an ingredient classifier, a plurality of ingredients to a plurality of impact factors. At least a processor is configured to generate, as a function of impact factors, an ingredient chain for a user.

Growing community of inventors

Lakewood, CO, United States of America

Kenneth Neumann