“System And Method For Determining And Presenting Clinical Answers” in Patent Application Approval Process (USPTO 20230043543): Healthpointe Solutions Inc.
2023 FEB 24 (NewsRx) -- By a
This patent application is assigned to
The following quote was obtained by the news editors from the background information supplied by the inventors: “Population health management entails aggregating patient data across multiple health information technology resources, analyzing the data with reference to a single patient, and generating actionable items through which care providers can improve both clinical and financial outcomes. A population health management service seeks to improve the health outcomes of a group by improving clinical outcomes while lowering costs.”
In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “Representative embodiments set forth herein disclose various techniques for enabling a system and method for determining and presenting clinical answers.
“In some embodiments, a method includes causing at least a portion of a knowledge graph representing ontological health related information to be presented on a display of a client device. The method further includes receiving, at an artificial intelligence engine, a medical query, wherein the medical query includes a plurality of strings of characters. The method further includes 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. The method further includes comparing the indicia to the knowledge graph to generate an answer responsive to the medical query. The method further includes causing the answer to be presented at the client device.
“In some embodiments, a method includes receiving an instruction to present at least a portion of a knowledge graph representing ontological health related information on a display of a device. The method further includes presenting the portion of the knowledge graph on the display of the device. The method further includes transmitting, to an artificial intelligence engine, a medical query, wherein the medical query includes a plurality of strings of characters. The method further includes receiving an answer responsive to the medical inquiry from the artificial intelligence engine The method further includes presenting the answer on the display of the device.
“In some embodiments, a system includes a memory storing instructions and a processor communicatively coupled with the memory. The processor may execute the instructions to perform one or more of the operations of the methods described above.
“In some embodiments, a tangible, non-transitory computer-readable medium stores instructions. A process may execute the instructions to perform one or more of the operations of the methods described above.”
The claims supplied by the inventors are:
“1. A method comprising: causing at least a portion of a knowledge graph representing ontological health related information to be presented on a display of a client device; receiving, at an artificial intelligence engine, a medical query, wherein the medical query 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 the knowledge graph to generate an answer responsive to the medical query; and causing the answer to be presented at the client device.
“2. The method of claim 1, wherein generating the answer further comprises: generating medical query information pertaining to the patient by comparing the indicia to the knowledge graph; identifying, using a logical structure, a structural similarity of the medical query information and a known predicate in the logical structure; and generating, by the artificial intelligence engine, the answer responsive to the medical query based on the structural similarity.
“3. The method of claim 1, further comprising: causing the answer to be presented via an audio output device, the display, or some combination thereof.
“4. The method of claim 1, further comprising: causing the portion of the knowledge graph to be modified by performing a visual drill-down from a first layer of information to a second layer of information and providing an indication for the answer, wherein the indication is highlighting, enlarged font, a parallax effect, zooming, bolding, underlining, increasing line weight, or some combination thereof.
“5. The method of claim 1, further comprising: identifying a role of a user; and wherein the answer generated by the artificial intelligence engine is based at least in part on the role of the user.
“6. The method of claim 1, wherein generating the answer further comprises generating a medical recommendation based on the knowledge graph and the medical query.
“7. The method of claim 1, wherein the knowledge graph contains ontological information pertaining to a condition of an individual patient.
“8. The method of claim 1, wherein generating the answer further comprises causing a graphical element to be presented that, when selected, causes an action to be performed pertaining to the medical query, wherein the action comprises scheduling an appointment, generating available appointments, causing curated medical content to be presented, or some combination thereof.
“9. A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to execute an artificial intelligence engine to: cause at least a portion of a knowledge graph representing ontological health related information to be presented on a display of a client device; receive, at an artificial intelligence engine, a medical query, wherein the medical query includes a plurality of strings of characters; identify, 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; compare the indicia to the knowledge graph to generate an answer responsive to the medical query; and causing the answer to be presented at the client device.
“10. The tangible, non-transitory computer-readable medium of claim 9, wherein generating the answer further comprises: generating medical query information pertaining to the patient by comparing the indicia to the knowledge graph; identifying, using a logical structure, a structural similarity of the medical query information and a known predicate in the logical structure; and generating, by the artificial intelligence engine, the answer responsive to the medical query based on the structural similarity.
“11. The tangible, non-transitory computer-readable medium of claim 9, wherein the instructions further cause the processing device to: cause the answer to be presented via an audio output device, the display, or some combination thereof.
“12. The tangible, non-transitory computer-readable medium of claim 9, wherein the instructions further cause the processing device to: causing the portion of the knowledge graph to be modified by performing a visual drill-down from a first layer of information to a second layer of information and providing an indication for the answer, wherein the indication is highlighting, enlarged font, a parallax effect, zooming, bolding, underlining, increasing line weight, or some combination thereof.
“13. The tangible, non-transitory computer-readable medium of claim 9, wherein the instructions further cause the processing device to: identify a role of a user; and wherein the answer generated by the artificial intelligence engine is based at least in part on the role of the user.
“14. The tangible, non-transitory computer-readable medium of claim 9, wherein generating the answer further comprises generating a medical recommendation based on the knowledge graph and the medical query.
“15. The tangible, non-transitory computer-readable medium of claim 9, wherein the knowledge graph contains ontological information pertaining to an individual patient.
“16. The tangible, non-transitory computer-readable medium of claim 9, wherein generating the answer further comprises causing a graphical element to be presented that, when selected, causes an action to be performed pertaining to the medical query, wherein the action comprises scheduling an appointment, generating available appointments, causing curated medical content to be presented, or some combination thereof.
“17. A system, comprising: a display; a memory device storing instructions; and a processing device operatively coupled to the memory device, wherein the processing device executes the instructions to: cause at least a portion of a knowledge graph representing ontological health related information to be presented on a display of a client device; receive, at an artificial intelligence engine, a medical query, wherein the medical query includes a plurality of strings of characters; identify, 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; compare the indicia to the knowledge graph to generate an answer responsive to the medical query; and cause the answer to be presented at the client device.
“18. The system of claim 17, wherein generating the answer further comprises: generating medical query information pertaining to the patient by comparing the indicia to the knowledge graph; identifying, using a logical structure, a structural similarity of the medical query information and a known predicate in the logical structure; and generating, by the artificial intelligence engine, the answer responsive to the medical query based on the structural similarity.
“19. The system of claim 17, wherein the processing device executes the instructions to: cause the answer to be presented via an audio output device, the display, or some combination thereof.
“20. The system of claim 17, wherein the processing device executes the instructions to: cause portion of the knowledge graph to be modified by performing a visual drill-down from a first layer of information to a second layer of information and providing an indication for the answer, wherein the indication is highlighting, enlarged font, a parallax effect, zooming, bolding, underlining, increasing line weight, or some combination thereof.
“21. The system of claim 17, wherein the processing device executes the instructions to: identify a role of a user; and wherein the answer generated by the artificial intelligence engine is based at least in part on the role of the user.
“22. The system of claim 17, wherein the generating the answer further comprises generating a medical recommendation based on the knowledge graph and the medical query.
“23. The system of claim 17, wherein the knowledge graph contains ontological information pertaining to a condition of an individual patient.
“24. The system of claim 17, wherein generating the answer further comprises causing a graphical element to be presented that, when selected, causes an action to be performed pertaining to the medical query, wherein the action comprises scheduling an appointment, generating available appointments, causing curated medical content to be presented, or some combination thereof.
“25. A method comprising: receiving an instruction to present at least a portion of a knowledge graph representing ontological health related information on a display of a device; presenting the portion of the knowledge graph on the display of the device; transmitting, to an artificial intelligence engine, a medical query, wherein the medical query includes a plurality of strings of characters; receiving an answer responsive to the medical inquiry from the artificial intelligence engine; and presenting the answer on the display of the device.
“26. The method of claim 25, wherein the answer is presented via an audio output device, the display, or some combination thereof.
“27. The method of claim 25, further comprising: modifying the portion of the knowledge graph by performing a visual drill-down from a first layer of information to a second layer of information and providing an indication for the answer, wherein the indication is highlighting, enlarged font, a parallax effect, zooming, or some combination thereof.
“28. The method of claim 25, further comprising: transmitting user information; and wherein the answer generated by the artificial intelligence engine is based at least in part on the user information.”
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