SYSTEM AND METHOD FOR COGNIFYING UNSTRUCTURED DATA

1 . A method comprising:

receiving, at an artificial intelligence engine, a corpus of data for a patient, wherein the corpus of data includes a plurality of strings of characters;

identifying, in the plurality of strings of characters, indicia comprising a phrase, a predicate, a keyword, a subject, an object, a cardinal, a number, a concept, or some combination thereof;

comparing the indicia to a knowledge graph representing known health related information to generate a possible health related information pertaining to the patient;

identifying, using a logical structure, a structural similarity of the possible health related information and a known predicate in the logical structure; and

generating, by the artificial intelligence engine, cognified data based on the structural similarity.

2 . The method of claim 1 , further comprising generating the knowledge graph using the known health related information, wherein the knowledge graph represents knowledge of a disease and the knowledge graph comprises a plurality of concepts pertaining to the disease obtained from the known health related information, and the knowledge graph comprises relationships between the plurality of concepts.

3 . The method of claim 1 , wherein the cognified data comprises a health related summary of the possible health related information.

4 . The method of claim 2 , wherein generating, by the artificial intelligence engine, the cognified data further comprises:

generating at least one new string of characters representing a statement pertaining to the possible health related information; and

including the at least one new string of characters in the health related summary of the possible health related information.

5 . The method of claim 4 , wherein the statement describes an effect that results from the possible health related information.

6 . The method of claim 1 , further comprising codifying evidence based health related guidelines pertaining to a disease to generate the logical structure.

7 . The method of claim 1 , further comprising:

identifying at least one piece of information missing in the corpus of data for the patient using the cognified data, wherein the at least one piece of information pertains to a treatment gap, a risk gap, a quality of care gap, or some combination thereof; and

causing a notification to be presented on a computing device of a healthcare personnel, wherein the notification instructs entry of the at least one piece of information.

8 . The method of claim 1 , wherein using the logical structure to identify the structural similarity of the indicia and the known predicate in the logical structure further comprises identifying, based on the structural similarity of the indicia and the known predicate in the logical structure, a treatment pattern, a referral pattern, a quality of care pattern, a risk adjustment pattern, or some combination thereof in the corpus of data.

9 . The method of claim 1 , further comprising:

receiving feedback pertaining to whether the cognified data is accurate; and

updating the artificial intelligence engine based on the feedback.

10 . A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to execute an artificial intelligence engine to:

receive a corpus of data for a patient, wherein the corpus of data includes a plurality of strings of characters;

identify, in the plurality of strings of characters, indicia comprising a phrase, a predicate, a keyword, a cardinal, a number, a concept, or some combination thereof;

compare the indicia to a knowledge graph representing known health related information to generate a possible health related information pertaining to the patient;

identify, using a logical structure, a structural similarity of the indicia and a known predicate in the logical structure; and

generate cognified data based on the similarity and the possible health related information.

11 . The computer-readable medium of claim 10 , wherein the artificial intelligence engine is further to generate the knowledge graph using the known health related information, wherein the knowledge graph represents knowledge of a disease and the knowledge graph comprises a plurality of concepts pertaining to the disease obtained from the known health related information, and the knowledge graph comprises relationships between the plurality of concepts.

12 . The computer-readable medium of claim 10 , wherein the cognified data comprises a health related summary of the possible health related information.

13 . The computer-readable medium of claim 12 , wherein generating, based on the pattern, the cognified data further comprises:

generating at least one new string of characters representing a statement pertaining to the possible health related information; and

including the at least one new string of characters in the health related summary of the possible health related information.

14 . The computer-readable medium of claim 13 , wherein the statement describes an effect that results from the possible health related information

15 . The computer-readable medium of claim 10 , wherein the artificial intelligence engine is further to codify evidence based health related guidelines pertaining to a disease to generate the logical structure.

16 . The computer-readable medium of claim 10 , wherein the artificial intelligence engine is further to:

identify at least one piece of information missing in the corpus of data for the patient using the cognified data, wherein the at least one piece of information pertains to a treatment gap, a risk gap, a quality of care gap, or some combination thereof; and

cause a notification to be presented on a computing device of a healthcare personnel, wherein the notification instructs entry of the at least one piece of information.

17 . The computer-readable medium of claim 10 , wherein using the logical structure to identify the structural similarity of the indicia and the known predicate in the logical structure further comprises identifying, based on the structural similarity of the indicia and the known predicate in the logical structure, a treatment pattern, a referral pattern, a quality of care pattern, a risk adjustment pattern, or some combination thereof in the corpus of data.

18 . The computer-readable medium of claim 10 , wherein the artificial intelligence engine is further to:

receive feedback pertaining to whether the cognified data is accurate; and

update the artificial intelligence engine based on the feedback.

19 . A system, comprising:

a memory device storing instructions; and

a processing device operatively coupled to the memory device, wherein the processing device executes the instructions to:

receive, at an artificial intelligence engine, a corpus of data for a patient, wherein the corpus of data includes a plurality of strings of characters;

identify, in the plurality of strings of characters, indicia comprising a phrase, a predicate, a keyword, a cardinal, a number, a concept, or some combination thereof;

compare the indicia to a knowledge graph representing known health related information to generate a possible health related information pertaining to the patient;

identify, using a logical structure, a structural similarity of the indicia and a known predicate in the logical structure; and

generate, by the artificial intelligence engine, cognified data based on the similarity and the possible health related information.

20 . The system of claim 19 , wherein the processing device is further to:

receive feedback pertaining to whether the cognified data is accurate; and

update the artificial intelligence engine based on the feedback.