Methods and systems for physiologically informed gestational inquiries
A system for physiologically informed gestational inquiries. The system includes a computing device configured to calculate a gestational phase, wherein the gestational phase is calculated by receiving a gestational datum, classifying the gestational datum to a gestational phase, and generating a gestational phase label. The computing device is further configured to receive from a remote device a gestational inquiry. The computing device is further configured to classify a gestational inquiry to an inquiry category. The computing device is further configured to select a gestational machine-learning model. The computing device is further configured to generate a gestational machine-learning model wherein the gestational machine-learning model utilizes a user biological extraction as an input and outputs gestational eligibility. The computing device is further configured to determine the gestational eligibility of a gestational inquiry.
1. A system for physiologically informed gestational inquiries, the system comprising a computing device the computing device designed and configured to:
calculate a gestational phase;
receive, from a remote device operated by a user, a gestational inquiry;
separate a gestational inquiry from a description of the gestational inquiry;
generate a gestational machine-learning model, wherein the gestational machine-learning model utilizes a gestational phase label and a user biological extraction as input and outputs a plurality of gestational eligibility labels; and
determine, utilizing the gestational machine-learning model, a gestational eligibility of the gestational inquiry.
2. The system of claim 1 , wherein calculating the gestational phase further comprises:
receiving a gestational datum;
classifying the gestational datum to the gestational phase; and
generating a gestational phase label as a function of the classifying.
3. The system of claim 2 , wherein classifying the gestational datum to the gestational phase further comprises generating a gestational classification algorithm, wherein the gestational classification algorithm utilizes the gestational datum as an input and outputs a gestational phase label.
4. The system of claim 1 , further comprising classifying the gestational inquiry to an inquiry category.
5. The system of claim 4 , further comprising selecting a gestational machine-learning model as a function of the inquiry category.
6. The system of claim 1 , wherein receiving the gestational inquiry further comprises receiving, at an image catching device located on the computing device, a wireless transmission from the remote device containing a picture of the gestational inquiry.
7. The system of claim 1 , wherein separating the gestational inquiry from the description of the gestational inquiry comprises utilizing a language processing module.
8. The system of claim 1 , wherein the biological extraction further comprises at least an element of physiological data.
9. The system of claim 8 , wherein the at least an element of physiological data comprises hematological data.
10. The system of claim 1 , wherein determining the gestational eligibility of the gestational inquiry further comprises evaluating at least a positive effect of the gestational inquiry on the user's biological extraction and gestational phase.
11. A method of physiologically informed gestational inquiries, the method comprising:
calculating, by a computing device, a gestational phase;
receiving by the computing device, from a remote device operated by a user, a gestational inquiry;
separating by the computing device, the gestational inquiry from a description of the gestational inquiry;
generating by the computing device, a gestational machine-learning model, wherein the gestational machine-learning model utilizes a gestational phase label and a user biological extraction as input and outputs a plurality of gestational eligibility labels; and
determining by the computing device, utilizing the gestational machine-learning model, a gestational eligibility of the gestational inquiry.
12. The method of claim 11 , wherein calculating the gestational phase further includes:
receiving a gestational datum;
classifying the gestational datum to the gestational phase; and
generating a gestational phase label as a function of the classifying.
13. The method of claim 12 , wherein classifying the gestational datum to the gestational phase further includes generating a gestational classification algorithm, wherein the gestational classification algorithm utilizes the gestational datum as an input and outputs a gestational phase label.
14. The method of claim 11 , further comprising classifying the gestational inquiry to an inquiry category.
15. The method of claim 14 , further comprising selecting by the computing device, a gestational machine-learning model as a function of the inquiry category.
16. The method of claim 11 , wherein receiving the gestational inquiry further includes receiving by the computing device, at an image catching device located on the computing device, a wireless transmission from the remote device containing a picture of the gestational inquiry.
17. The method of claim 11 , wherein separating the gestational inquiry from the description of the gestational inquiry includes utilizing a language processing module.
18. The method of claim 11 , wherein the biological extraction further includes at least an element of physiological data.
19. The method of claim 18 , wherein the at least an element of physiological data includes hematological data.
20. The method of claim 11 , wherein determining the gestational eligibility of the gestational inquiry further includes evaluating at least a positive effect of the gestational inquiry on the user's biological extraction and gestational phase.