US 12,412,670 B2
System and method for defining a user experience of medical data systems through a knowledge graph
Nathan Gnanasambandam, Irvine, CA (US); and Mark Henry Anderson, Newport Coast, CA (US)
Assigned to HEALTHPOINTE SOLUTIONS, INC., Austin, TX (US)
Appl. No. 17/638,131
Filed by HEALTHPOINTE SOLUTIONS, INC., Austin, TX (US)
PCT Filed Aug. 21, 2020, PCT No. PCT/US2020/047480
§ 371(c)(1), (2) Date Feb. 24, 2022,
PCT Pub. No. WO2021/041241, PCT Pub. Date Mar. 4, 2021.
Application 17/638,131 is a continuation in part of application No. 16/593,491, filed on Oct. 4, 2019, granted, now 11,263,405.
Claims priority of provisional application 62/891,677, filed on Aug. 26, 2019.
Prior Publication US 2022/0375622 A1, Nov. 24, 2022
Int. Cl. G16H 50/70 (2018.01); G16H 10/60 (2018.01)
CPC G16H 50/70 (2018.01) [G16H 10/60 (2018.01)] 15 Claims
OG exemplary drawing
 
1. A method for controlling distribution of a plurality of information pertaining to a medical condition, the method comprising:
receiving, at a server, an electronic medical record comprising notes pertaining to a patient;
processing the notes to obtain indicia by inputting the notes into an artificial intelligence engine trained to identify the indicia in text based on commonly used indicia pertaining to the medical condition, wherein the indicia comprising a word, a cardinal, a phrase, a sentence, a predicate, or some combination thereof;
generating, based on the indicia using the artificial intelligence engine and a knowledge graph, a cognified data structure comprising a diagnosis of a possible medical condition of the patient by identifying a similarity between the indicia and the knowledge graph representing knowledge pertaining to the possible medical condition, wherein:
(i) the knowledge graph comprises a plurality of nodes representing a plurality of information pertaining to the possible medical condition,
(ii) the possible medical condition is diagnosed based on a threshold number of matches between the indicia and the plurality of nodes representing the plurality of information in the knowledge graph, and
(iii) the cognified data structure identifies at least a treatment gap pertaining to the possible medical condition;
providing, at a first time, first information of the plurality of information to a computing device of the patient for presentation on the computing device, the first information being associated with a root node of the plurality of nodes;
providing, at a second time, second information of the plurality of information to the computing device of the patient for presentation on the computing device, the second information being associated with a second node of the plurality of nodes, and the second time being after the first time;
identifying a second possible medical condition of the patient by identifying a second similarity between the indicia and a second knowledge graph representing second knowledge pertaining to the second possible medical condition, wherein the second knowledge graph comprises a second plurality of nodes representing a second plurality of information pertaining to the second possible medical condition; and
providing, at the first time, second information of the second plurality of information to the computing device of the patient for presentation on the computing device, the second information being associated with a second root node of the second plurality of nodes.