System and method for generating a digestive disease nourishment program

1. A system for generating a digestive disease nourishment program, the system comprising: a computing device, the computing device configured to:

receive at least a digestive biomarker relating to a user;

generate at least a digestive parameter as a function of the at least a digestive disease biomarker;

determine a digestive profile as a function of the at least a digestive parameter;

identify at least a nutrition element as a function of the digestive profile, wherein identifying comprises:

determining, for each nutrition element of a plurality of nutrition elements, a nourishment score as a function of the effect of the nutrition element on the digestive profile;

generating training data as a function of the plurality of nutrition elements, wherein the training data correlates each nourishment score to a nutrient composition for each nutritional element of the plurality of nutrition elements;

training a machine-learning model as a function of a machine-learning process and the training data;

identifying a first nutrient composition as a function of the machine-learning model;

receiving a nourishment training set correlating nutrition elements to nutrient compositions;

training a classification machine-learning process as a function of the nourishment training set; and

classifying the at least a nutrition element to a class including the first nutrient composition as a function of the classification machine-learning process and the first nutrient composition; and

generate a digestive disease nourishment program as a function of the nutrition element and the digestive profile.

2. The system of claim 1 , wherein receiving the at least the digestive biomarker comprises receiving a result of one or more tests relating the user.

3. The system of claim 1 , wherein receiving the at least the digestive biomarker comprises receiving a prior diagnosis of a digestive disease relating to the user.

4. The system of claim 1 , wherein identifying the at least a nutrition element comprises:

classifying the digestive profile to a digestive disease category, wherein:

the digestive profile includes a quantitative digestive health score correlated to the at least a digestive parameter; and

the digestive profile includes an absorption condition correlated to the at least a digestive parameter; and

identifying the at least a nutrition element according to the digestive disease category.

5. The system of claim 4 , wherein identifying the at least a nutrition element further comprises identifying at least a nutrition element intended to prevent digestive disease according to the digestive disease category.

6. The system of claim 1 , wherein generating the digestive disease nourishment program comprises:

receiving at least a user preference regarding the at least a nutrition element; and

modifying the at least a nutrition element as a function of the at least a user preference.

7. The system of claim 1 , wherein identifying the nutrition elements comprises identifying nutrition elements that have a positive impact on an absorption condition.

8. The system of claim 7 , wherein the absorption condition is correlated to increased intestinal permeability.

9. A method for generating a digestive disease nourishment program, the method comprising:

receiving at least a digestive biomarker relating to a user;

generating at least a digestive parameter of a plurality of digestive parameters as a function of the digestive disease biomarker;

determining a digestive profile as a function of the at least a digestive parameter;

identifying at least a nutrition element as a function of the digestive profile, wherein identifying comprises:

determining, for each nutrition element of a plurality of nutrition elements, a nourishment score as a function of the effect of the nutrition element on the digestive profile;

generating training data as a function of the plurality of nutrition elements, wherein the training data correlates each nourishment score to a nutrient composition for each nutritional element of the plurality of nutrition elements;

training a machine-learning model as a function of a machine-learning process and the training data;

identifying a first nutrient composition as a function of the machine-learning model;

receiving a nourishment training set correlating nutrition elements to nutrient compositions;

training a classification machine-learning process as a function of the nourishment training set;

classifying the at least a nutrition element to a class including the first nutrient composition as a function of the classification machine-learning process and the first nutrient composition; and

generating a digestive disease nourishment program as a function of the nutrition element and the digestive profile.

10. The method of claim 9 , wherein receiving at least the digestive biomarker comprises receiving a result of one or more tests relating the user.

11. The method of claim 9 , wherein receiving at least the digestive biomarker comprises receiving a prior diagnosis of a digestive disease relating to the user.

12. The method of claim 9 , wherein identifying the at least a nutrition element comprises:

classifying the digestive profile to a digestive disease category, wherein:

the digestive profile includes a quantitative digestive health score correlated to the at least a digestive parameter; and

the digestive profile includes an absorption condition correlated to the at least a digestive parameter; and

identifying the at least a nutrition element according to the digestive disease category.

13. The method of claim 12 , wherein identifying the at least a nutrition element comprises identifying at least a nutrition element intended to prevent digestive disease according to the digestive disease category.

14. The method of claim 9 , wherein generating the digestive disease nourishment program comprises:

receiving at least a user preference regarding the at least a nutrition element; and

modifying the at least a nutrition element as a function of the at least a user preference.

15. The method of claim 9 , wherein identifying the nutrition elements comprises identifying nutrition elements that have a positive impact on an absorption condition.

16. The method of claim 15 , wherein the absorption condition is correlated to increased intestinal permeability.