Artificial intelligence advisory systems and methods for providing health guidance

1. An artificial intelligence constitutional advisory system, the system comprising:

at least a server;

a diagnostic engine operating on the at least a server, wherein the diagnostic engine is configured to:

record at least a biological extraction from a user, wherein the at least a biological extraction includes a signal from at least a sensor configured to detect physiological data of the user, and wherein the at least a sensor is included in the diagnostic engine; and

generate, using at least a machine learning algorithm, a diagnostic output based on the at least a biological extraction, the diagnostic output including at least a prognostic label and at least an ameliorative process label, wherein the diagnostic output identifies a condition of the user;

an advisory module operating on the at least a server, wherein the advisory module is configured to:

receive a user textual input from a user client device associated with the user using an instant messaging protocol;

receive an answer to a user clarification question from the user client device associated with the user using the instant messing protocol, wherein the answer to the user clarification question comprises a selection; and

transmit at least a textual output to the user client device associated with the user using the instant messaging protocol; and

an artificial intelligence advisor operating on the at least a server, wherein the artificial intelligence advisor has a parsing module configured to generate at least a query, using the user textual input, and a processing module configured to generate the at least a textual output, as a function of the at least a query, wherein the parsing module is further configured to extract a conversational query and an informational query from the user textual input and identify the conversational query and the informational query to the processing module, and wherein the artificial intelligence advisor is configured to generate the at least a textual output using the diagnostic output and the user textual input, wherein the artificial intelligence advisor further comprises a consultation initiator configured to:

map, using a machine-learning process, a combination of a phrase with a second prognostic label to a need to consult with a doctor;

add the combination of the phrase and the second prognostic label to a keyword listing combining keywords with prognostic labels;

generate the user clarification question based upon the user textual input, wherein the user clarification question comprises a prompt for the selection;

detect the need to consult with the doctor in the user textual input, wherein detecting the need to consult with the doctor further comprises:

comparing a phrase extracted from the user textual input, the selection, and the second prognostic label to the identified condition of the user; and

detecting, based on the comparison, the need to consult with a doctor; and

initiate a consultation with a doctor as a function of the need to consult with a doctor.

2. The artificial intelligence advisory system of claim 1 , wherein the parsing module further comprises a language processing module configured to map the user textual input to the at least a query.

3. The artificial intelligence advisory system of claim 1 , wherein the processing module is further configured to:

generate a conversational response using the conversational query.

4. The artificial intelligence advisory system of claim 3 , wherein the processing module is further configured to:

retrieve at least a datum from a default response database using the conversational query; and

generate the conversational response using the at least a datum.

5. The artificial intelligence advisory system of claim 3 , wherein the processing module further includes a user communication learner configured to generate the at least a conversational response using the conversational query.

6. The artificial intelligence advisory system of claim 1 , wherein the processing module is further configured to:

generate an informational response using the informational query.

7. The artificial intelligence advisory system of claim 6 , wherein the processing module is further configured to:

retrieve at least a datum from the diagnostic output using the informational query; and

generate the informational response using the at least a datum.

8. The artificial intelligence advisory system of claim 6 , wherein the processing module is further configured to:

retrieve at least a datum from a user database using the informational query; and

generate the informational response using the at least a datum.

9. The artificial intelligence advisory system of claim 6 , wherein the processing module is further configured to:

input the informational query to a prognostic label learner operating on the at least a server, wherein the prognostic label learner is designed and configured to generate at least a prognostic output as a function of the informational query and a training set correlating physiological state data to prognostic labels;

receive, from the prognostic label learner, the at least a prognostic output; and

generate the informational response using the at least a prognostic output.

10. The artificial intelligence advisory system of claim 6 , wherein the processing module is further configured to:

input the informational query to an ameliorative process label learner operating on the at least a server, wherein the ameliorative process label learner is designed and configured to generate at least an ameliorative output as a function of the informational query and a training set correlating prognostic labels to ameliorative process labels;

receive, from the ameliorative process label learner, the at least an ameliorative output; and

generate the informational response using the at least an ameliorative output.

11. The artificial intelligence advisory system of claim 6 , wherein generating the informational response further comprises:

generating a plurality of informational responses using a first informational resource;

retrieving at least an additional datum from at least a second informational resource; and

selecting an informational response from the plurality of informational responses, using the at least an additional datum.

12. The artificial intelligence advisory system of claim 1 , wherein the processing module is further configured to:

generate a conversational response using the conversational query;

and

combine the conversational response and the informational response.

13. The artificial intelligence advisory system of claim 1 , wherein initiating the consultation with the doctor further comprises:

detecting, in the keyword listing, a flag indicating that the need to consult with the doctor requires an emergency call; and

automatically placing the emergency call as a result of the detection.

14. The artificial intelligence advisory system of claim 1 , wherein the machine learning algorithm includes a decision tree algorithm.

15. The artificial intelligence advisory system of claim 1 , wherein the machine learning algorithm includes a gradient tree boosting algorithm.

16. An artificial intelligence method of generating constitutional advice, the method comprising:

recording, by a diagnostic engine operating on at least a server, at least a biological extraction from a user, wherein the at least a biological extraction includes a signal from at least a sensor configured to detect physiological data of the user, and wherein the at least a sensor is included in the diagnostic engine;

generating, by the diagnostic engine, and using at least a machine-learning algorithm, a diagnostic output based on the at least a biological extraction, the diagnostic output including at least a prognostic label and at least an ameliorative process label, wherein the diagnostic output identifies a condition of the user;

receiving, by an advisory module operating on the at least a server, a user textual input via an instant messaging protocol from a user client device associated with the user;

receiving, by the advisory module operating on the at least a server, an answer to a user clarification question from the user client device associated with the user using the instant messaging protocol, wherein the answer to the user clarification question comprises a selection;

transmitting, by the advisory module, at least a textual output to the user client device associated with the user using the instant messaging protocol;

generating, by an artificial intelligence advisor, at least a textual output using the diagnostic output and the user textual input, wherein the artificial intelligence advisor has a parsing module configured to generate at least a query, using the user textual input, and a processing module configured to generate the at least a textual output, as a function of the at least a query, wherein the parsing module is further configured to extract a conversational query and an informational query from the user textual input and identify the conversational query and the informational query to the processing module;

mapping, by a consultation initiator of the artificial intelligence advisor, using a machine-learning process, a combination of a phrase with a second prognostic label to a need to consult with a doctor;

adding, by the consultation initiator, the combination of the phrase and the second prognostic label to a keyword listing combining keywords with prognostic labels;

generating, by the consultation initiator, the user clarification question based upon the user textual input, wherein the user clarification question comprises a prompt for the selection;

detecting, by the consultation initiator, the need to consult with the doctor in the user textual input, wherein detecting the need to consult with the doctor further comprises:

comparing a phrase extracted from the user textual input, the selection, and the second prognostic label to the identified condition of the user; and

detecting, based on the comparison, the need to consult with a doctor; and

initiating, by the consultation initiator, a consultation with a doctor as a function of the need to consult with a doctor.

17. The artificial intelligence method of claim 16 further comprising:

generating a conversational response using the conversational query.

18. The artificial intelligence method of claim 16 , further comprising:

generating an informational response using the informational query.

19. The artificial intelligence advisory method of claim 18 further comprising:

inputting the informational query to a prognostic label learner operating on the at least a server, wherein the prognostic label learner is designed and configured to generate at least a prognostic output as a function of the informational query and a training set correlating physiological state data to prognostic labels;

receiving, from the prognostic label learner, the at least a prognostic output; and

generating the informational response using the at least a prognostic output.

20. The artificial intelligence advisory method of claim 18 further comprising:

inputting the informational query to an ameliorative process label learner operating on the at least a server, wherein the ameliorative process label learner is designed and configured to generate at least an ameliorative output as a function of the informational query and a training set correlating prognostic labels to ameliorative process labels;

receiving, from the ameliorative process label learner, the at least an ameliorative output; and

generating the informational response using the at least an ameliorative output.