Artificial intelligence systems and methods for generating educational inquiry responses from biological extractions
An artificial intelligence system for generating educational inquiry responses from biological extractions, the system comprising a computing device, the computing device designed and configured to retrieve a biological extraction pertaining to a user, receive, from a third-party device, an educational inquiry, select, based on the educational inquiry, at least a machine-learning process, and generate, using the at least a machine-learning process and the biological extraction, an inquiry response.
1. An artificial intelligence system for generating educational inquiry responses from biological extractions, the system comprising a computing device, the computing device designed and configured to:
retrieve a biological extraction pertaining to a user, wherein the biological extraction comprises a genetic body measurement of neurotrophic factor production;
identify, based on the biological extraction, at least a psychological need of the user, wherein the at least a psychological need of the user is determined using a plurality of assessments, and wherein the plurality of assessments comprises a genetic test;
receive, from a third-party device, an educational inquiry comprising an inquiry regarding mental health supports at an institution;
select, based on the educational inquiry, at least a machine-learning model, receive biological extraction training data correlating biological extractions to learning disability support programs;
train the at least a machine-learning model with biological extraction training data correlating biological extractions to learning disability support programs; and
generate, using the at least a machine-learning model and the identified psychological need of the user, an inquiry response.
2. The system of claim 1 , wherein the biological extraction includes a psychological profile.
3. The system of claim 2 , wherein the psychological profile is obtained utilizing a questionnaire performed by the user.
4. The system of claim 1 , wherein the biological extraction includes a genetic sequence.
5. The system of claim 1 , wherein the educational inquiry is an inquiry regarding a suitable educational institution.
6. The system of claim 1 , wherein the educational inquiry is an inquiry regarding a suitable form of instruction.
7. The system of claim 1 , wherein the educational inquiry is an inquiry regarding a learning style of the user.
8. The system of claim 1 , wherein the computing device is further configured to select the at least a machine-learning model using a classifier that inputs the educational inquiry and outputs at least a machine-learning model.
9. The system of claim 1 , wherein the computing device is further configured to select the at least a machine-learning model as a function of the biological extraction.
10. The system of claim 1 , wherein the at least a machine-learning model further includes a mental health suitability classification process.
11. An artificial intelligence method of generating educational inquiry responses from biological extractions, the method comprising:
retrieving, by a computing device, a biological extraction pertaining to a user, wherein the biological extraction comprises a genetic body measurement of neurotrophic factor production;
identifying, by the computing device, based on the biological extraction, at least a psychological need of the user, wherein the at least a psychological need of the user is determined using a plurality of assessments, and wherein the plurality of assessments comprises a genetic test;
receiving, by the computing device and from a third-party device, an educational inquiry comprising an inquiry regarding mental health supports at an institution;
selecting, by the computing device and based on the educational inquiry, at least a machine-learning model;
receiving, at the computing device, biological extraction training data correlating biological extractions to learning disability support programs;
training the at least a machine-learning model with the biological extraction training data; and
generating, by the computing device and using the at least a machine-learning model and the identified psychological need of the user, an inquiry response.
12. The method of claim 11 , wherein the biological extraction includes a psychological profile.
13. The method of claim 12 , wherein the psychological profile is obtained utilizing a questionnaire performed by the user.
14. The method of claim 11 , wherein the biological extraction includes a genetic sequence.
15. The method of claim 11 , wherein the educational inquiry is an inquiry regarding a suitable educational institution.
16. The method of claim 11 , wherein the educational inquiry is an inquiry regarding a suitable form of instruction.
17. The method of claim 11 , wherein the educational inquiry is an inquiry regarding a learning style of the user.
18. The method of claim 11 , wherein selecting the at least a machine-learning model further comprises selecting the at least a machine-learning model using a classifier that inputs the educational inquiry and outputs at least a machine-learning model.
19. The method of claim 11 , wherein selecting the at least a machine-learning model further comprises selecting the at least a machine-learning model as a function of the biological extraction.
20. The method of claim 11 , wherein the at least a machine-learning model further includes a mental health suitability classification process.