Abstract: Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, a treatment plan for a medical condition of a patient. The method comprises receiving medical data pertaining to the patient. The method also comprises determining, by the artificial intelligence engine and by using machine learning models, a disease progression level for the medical condition of the patient. The disease progression level indicates a risk of the patient reaching a next stage on a disease continuum of the medical condition. The method further comprises generating, by the artificial intelligence engine, the treatment plan for the medical condition. The generating is based at least on the disease progression level. The treatment plan comprises one or more actionable items to be performed on or by the patient. The method also comprises transmitting the treatment plan to a computing device for presentation to a healthcare professional.

Abstract: A method for electronically generating a care plan is disclosed. The method includes selecting a first data structure corresponding to a first condition of a patient. The first data structure including a set of health artifacts pertaining to the first condition. The method also including comparing a second data structure with the first data structure. The second data structure pertains to the patient and the first condition of the patient, and the second data structure comprises a subset of the set of health artifacts. The method also including selecting, based on the comparing, another subset of the set of health artifacts in the first data structure, generating the care plan comprising a third data structure that includes at least the another subset of the set of health artifacts, and causing the care plan to be presented on a computing device.

Abstract: A method for electronically generating a care plan is disclosed herein. The method includes comparing a first data structure with a second data structure. The first data structure includes a set of health artifacts pertaining to a first condition of the patient. The second data structure pertains to the patient and the first condition of the patient, and the second data structure includes a subset of the set of the health artifacts. Responsive to the comparing, the method also includes generating the care plan comprising another subset of the set of health artifacts, and modifying the another subset of the set of health artifacts in the care plan based on a detected tone of the patient, a detected emotion of the patient, a medical outcome desired by a physician, or some combination thereof.

Abstract: A computer-implemented method is performed by a cognitive intelligence platform. The method comprises: receiving, from a plurality of electronic health record systems, medical records associated with medical encounters of a patient with one or more medical providers over a period of time, the medical records including medical information related to care of the patient; analyzing the medical records by classifying the medical information included in the medical records into medical entities, the medical entities including categories having particular shared characteristics related to the care of the patient; determining, based on the medical entities, an effectiveness of a treatment plan received by the patient; generating an indication of the effectiveness of the treatment plan; and providing the indication to a user interface executing on a computing device.

Abstract: A computer-implemented method performed by a cognitive intelligence platform is disclosed herein. The method comprises: receiving, from a plurality of electronic health record systems, medical records associated with medical encounters of a patient with one or more medical providers over a period of time, the medical records including medical information related to care of the patient; analyzing the medical records by classifying the medical information included in the medical records into medical entities, the medical entities including categories having particular shared characteristics related to the care of the patient; generating, based on the medical entities, visual representations of the medical records over the period of time; and providing the visual representations of the medical records to a medical provider.

Abstract: A node that is part of a network of nodes with access to a distributed ledger may receive a transaction request to perform one or more operations associated with the distributed ledger, wherein the one or more operations include causing a record of a transaction to be stored using the distributed ledger. The node may determine, based on credential information associated with the transaction request, whether to allow the one or more operations to be performed. The node may perform the one or more operations based on determining to allow the one or more operations to be performed. The one or more operations may include adding the record of the transaction to the distributed ledger. At least a subset of the content may be included in the record. The node may cause one or more other nodes, of the network of nodes, to have access to the distributed ledger.

Abstract: A method for determining a risk for an infectious disease for a patient using a cognitive intelligence platform is disclosed. The method includes receiving, from an authoritative source, factors indicative of a person being infected by the infectious disease, wherein the factors include medical information pertaining to the infectious disease. The method also includes determining whether any of the factors are present in a patient graph of the patient, wherein the patient graph includes medical information pertaining to the patient and the determining is performed by matching the medical information pertaining to the infectious disease to the medical information pertaining to the patient. The method also includes, responsive to determining the factors are present in the patient graph of the patient, determining the risk for the infectious disease for the patient, and performing a preventative action based on the risk for the infectious disease.

Abstract: A computer-implemented method for real-time detection, by a participant in a health information exchange, of unap-proved uses of health information is disclosed. The method comprises: building a knowledge graph representing relationships between characteristics of health related information of a patient; receiving, from a second participant, a request for access to health information of the patient; generating, using the knowledge graph, questions about the characteristics of health related information of the patient for the second participant to answer to confirm authenticity of the request; and providing access to the health information to the second participant based on the second participant providing correct responses to the questions.

Abstract: A method for controlled and trust-aware contact tracing using a distributed ledger is disclosed herein. The method comprises: receiving, by a node that is part of a network of nodes with access to the distributed ledger, a notification that a person has been admitted to a gathering of people; generating a key associated with the gathering; prompting the person to enter the key associated with the gathering into a user interface of a computing device; in response to the person entering the key, tagging the person with an identifier associated with a location and a time of the person being admitted to the gathering; and performing one or more operations on the distributed ledger, wherein the one or more operations comprises storing a record of a transaction of admitting the person to the gathering and information associated with the transaction of admitting the person in the distributed ledger.

Abstract: A method for detecting unapproved uses of medical records stored in a distributed ledger at one or more nodes of a network of the distributed ledger is disclosed. The method comprises: receiving, from a first node of the one or more nodes, a request to perform a transaction on the distributed ledger, where the request includes an organization type of an entity associated with the first node, a transaction type of the transaction, and a use type for the transaction; and determining whether the use type for the transaction is permitted for the organization type of the entity. The method further comprises, responsive to determining the use type for the transaction is permitted for the organization type of the entity, executing a function defined for the organization type and the transaction type to perform the transaction on the distributed ledger.

Abstract: A method for maintaining content pertaining to a medical condition for a patient in a distributed ledger is disclosed. The method comprises: determining whether content pertaining to the medical test is corroborated by one or more records of other transactions associated with a patient that are stored in the distributed ledger; responsive to determining that the content pertaining to the medical test is corroborated, endorsing the transaction request; determining whether a threshold number of nodes of the network of nodes have endorsed the transaction request; and responsive to determining that the threshold number of nodes of the network of nodes have endorsed the transaction request, performing the one or more operations to store the record of the transaction associated with the medical test for the patient and the content pertaining to the medical test for the patient in the distributed ledger.

Abstract: A method for monitoring a risk of infectious disease for a patient using a patient viewer provided by a cognitive intelligence platform is disclosed. The method includes receiving a selection to estimate the risk of infectious disease for the patient, presenting, via the patient viewer, a question pertaining to a symptom of the infectious disease in a conversational interface, receiving an answer to the question, transmitting the answer, receiving, from the cognitive intelligence platform, the risk for the infectious disease, where the risk is determined in real-time by the cognitive intelligence platform based on a combination of the answer and a patient graph of the patient maintained by the cognitive intelligence platform, the patient graph including another symptom of the patient obtained from an electronic medical record system, and presenting the risk for the infectious disease in the conversational interface of the patient viewer on the computing device.

Abstract: A system and a method directed to image and information extraction to make decisions using curated medical knowledge are disclosed. For example, operations performed by a cognitive intelligence platform include receiving, from a user computing device, image data of an object and processing the image data to extract data pertaining to the object, where the data comprises text, an image, or some combination thereof. The operations further include identifying a data structure comprising health information pertaining to a user operating the user computing device, where the data structure is stored in a knowledge cloud of the cognitive intelligence platform. The operations also include populating a parameter in the data structure with the data and causing, using the parameter, a field to be populated on a user interface presented on the user computing device.

Abstract: A device receives patient data that indicates health related information associated with a patient. The device identifies, by processing the patient data using one or more natural language processing techniques, indicia associated with a health status of the patient. The device identifies similarities between the indicia and the content. The device generates, using an artificial intelligence engine, cognified data based on the similarities. The device identifies a medical code that correlates to particular content that is similar to the indicia. The device causes the cognified data to be displayed in association with medical code.

Abstract: A method for dynamically managing a goal in a care plan of a patient is disclosed. The method includes receiving a selection of a type of the care plan for the patient, responsive to the selection of the type of the care plan, receiving a selection of a goal having a goal type to include in the care plan, generating the care plan including the goal having the goal type, and causing the care plan including the goal to be presented on a computing device of a medical personnel.

Abstract: A method for autonomously generating a care plan personalized for a patient is disclosed. The method includes receiving a selection of a type of the care plan to implement for the patient, generating the care plan based on the type selected, wherein the care plan includes an action instruction based on a patient graph of the patient and a knowledge graph including ontological medical data, receiving patient data that indicates health related information associated with the patient, modifying the care plan to generate a modified care plan in real-time or near real-time based on the patient data, and causing the modified care plan to be presented on a computing device of a medical personnel.

Abstract: 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.

Abstract: In one embodiment, a method is disclosed for presenting a user interface including clustered event episode bundles pertaining to a medical condition. The method includes receiving, from a server, the clustered event episode bundles comprising event information clustered into an episode based on when events occurred and a taxonomy of ontological medical knowledge, presenting, via the user interface, a timeline that represents a period of time, and presenting, via the user interface, the clustered event episode bundles pertaining to each patient of a plurality of patients in a respective band relative to the timeline.

Abstract: In one embodiment, a method for operating an artificial intelligence engine is disclosed. The method may include determining a shared medical condition state for a subset of a population of people, segmenting the population of the people into a registry of people based on the shared medical condition state, determining an action to perform for the registry of the people based on comparing the shared medical condition state to ontological medical information, and autonomously performing, by the artificial intelligence engine, the action for the registry of the people.

Abstract: A system and a method directed to various techniques for creating an autonomous multipurpose application using a platform of application programming interfaces (APIs). In one embodiment, a method comprising operations performed by a cognitive intelligence platform is disclosed. The method includes: publishing, for implementation in the autonomous multipurpose application, at least one API that uses artificial intelligence to perform analytics based on a knowledge graph pertaining to ontological data of a medical condition, wherein the at least one API is included in a set of APIs; providing the at least one API in a user interface of a computing device; receiving, from the computing device, a request to subscribe to the at least one API; implementing computer instructions of the at least one API in the autonomous multipurpose application; and providing the autonomous multipurpose application to the computing device for execution on the computing device.