METHODS AND SYSTEMS FOR NUTRITIONAL RECOMMENDATION USING ARTIFICIAL INTELLIGENCE ANALYSIS OF IMMUNE IMPACTS
A system for nutritional recommendation using artificial intelligence analysis of immune impacts includes a computing device designed and configured to receive a test result detecting an effect of at least an aliment on at least a biomarker, determine an immune system impact of the at least an aliment as a function of the at least a biomarker using a machine-learning process, the machine-learning process trained using a first training set relating biomarker levels to immune system function, generate a nutritional recommendation using the determined immune system impact, and provide the nutritional recommendation to the user.
1 . A system for nutritional recommendation using artificial intelligence analysis of immune impacts, the system comprising a computing device designed and configured to:
receive a behavioral datum of a user;
receive a test result detecting an effect of at least the behavioral datum on at least a biomarker;
generate a machine-learning model, wherein generating the machine-learning model comprises:
receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and
training a machine-learning process as a function of the first training set to generate the machine-learning model;
determine an immune system impact of the behavioral datum as a function of the at least a biomarker using the machine-learning model;
generate a nutritional recommendation using the determined immune system impact; and
provide the nutritional recommendation to the user.
2 . The system of claim 1 , wherein receiving the behavioral datum of the user comprises receiving the behavioral datum from a wearable device of the user.
3 . The system of claim 2 , wherein providing the nutritional recommendation to the user comprises displaying the nutritional recommendation to the user on a display of the wearable device.
4 . The system of claim 1 , wherein:
the behavioral datum comprises a sleep cycle datum; and
receiving the test result comprises receiving the test result detecting an effect of the sleep cycle datum on the at least a biomarker.
5 . The system of claim 1 , wherein:
the behavioral datum comprises an exercise datum; and
receiving the test result comprises receiving the test result detecting an effect of the exercise datum on the at least a biomarker.
6 . The system of claim 1 , wherein receiving the test result comprises receiving a result of a differential test, wherein the result of the differential test shows the effect of the behavioral datum on one or more biomarkers of the user.
7 . The system of claim 1 , wherein the computing device is further configured to select the first training set, wherein selecting the first training set comprises:
receiving at least an element of user data describing the user;
identifying a plurality of data entries matching the at least an element of user data; and
selecting the first training set from the plurality of data entries matching the at least an element of user data.
8 . The system of claim 1 , wherein generating the nutritional recommendation comprises:
identifying whether the behavioral datum has a positive immune effect;
retrieving a list of related behavioral data as a function of the identification; and
generating a nutritional recommendation as a function of the list of related behavior data.
9 . The system of claim 1 , wherein the computing device is further configured to generate a physiological stimulus recommendation using the determined immune system impact.
10 . The system of claim 9 , wherein the computing device is further configured to provide the physiological stimulus recommendation to the user, wherein:
providing the physiological stimulus recommendation comprises transmitting the physiological stimulus recommendation to a wearable device; and
the physiological stimulus recommendation comprises a user prompt.
11 . A method of nutritional recommendation using artificial intelligence analysis of immune impacts, the method comprising:
receiving, by a computing device, a behavioral datum of a user;
receiving, by the computing device, a test result detecting an effect of at least the behavioral datum on at least a biomarker;
generating, by the computing device, a machine-learning model, wherein generating the machine-learning model comprises:
receiving a first training set, wherein the first training set correlates biomarker levels to immune system function; and
training a machine-learning process as a function of the first training set to generate the machine-learning model;
determining, by the computing device, an immune system impact of the behavioral datum as a function of the at least a biomarker using the machine-learning model;
generating, by the computing device, a nutritional recommendation using the determined immune system impact; and
providing, by the computing device, the nutritional recommendation to the user.
12 . The method of claim 11 , wherein receiving the behavioral datum of the user comprises receiving the behavioral datum from a wearable device of the user.
13 . The method of claim 12 , wherein providing the nutritional recommendation to the user comprises displaying the nutritional recommendation to the user on a display of the wearable device.
14 . The method of claim 11 , wherein:
the behavioral datum comprises a sleep cycle datum; and
receiving the test result comprises receiving the test result detecting an effect of the sleep cycle datum on the at least a biomarker.
15 . The method of claim 11 , wherein:
the behavioral datum comprises an exercise datum; and
receiving the test result comprises receiving the test result detecting an effect of the exercise datum on the at least a biomarker.
16 . The method of claim 11 , wherein receiving the test result comprises receiving a result of a differential test, wherein the result of the differential test shows the effect of the behavioral datum on one or more biomarkers of the user.
17 . The method of claim 11 , further comprising selecting, by the computing device, the first training set, wherein selecting the first training set comprises:
receiving at least an element of user data describing the user;
identifying a plurality of data entries matching the at least an element of user data; and
selecting the first training set from the plurality of data entries matching the at least an element of user data.
18 . The method of claim 11 , wherein generating the nutritional recommendation comprises:
identifying whether the behavioral datum has a positive immune effect;
retrieving a list of related behavioral data as a function of the identification; and
generating a nutritional recommendation as a function of the list of related behavior data.
19 . The method of claim 11 , further comprising generating, by the computing device, a physiological stimulus recommendation using the determined immune system impact.
20 . The method of claim 19 , further comprising providing, by the computing device, the physiological stimulus recommendation to the user, wherein:
providing the physiological stimulus recommendation comprises transmitting the physiological stimulus recommendation to a wearable device; and
the physiological stimulus recommendation comprises a user prompt.