Cognitive systems for allocating medical data access permissions using historical correlations
First Claim
1. A computer-implemented method for allocating medical data access permissions using historical correlations, the computer-implemented method comprising:
- receiving, by a computing system comprising one or more processors, a request for first medical research data from a first user;
executing, by the computing system, natural language processing to interpret the request;
generating, by the computing system, a database query based on a trained model to identify a first medical research data set that is responsive to the request, wherein the trained model takes into consideration (a) results of the natural language processing of the received request and (b) prior medical research data requests and responses that are stored in a historical database;
querying, by the computing system, one or more medical databases using the query to identify the first medical research data set that is responsive to the request, wherein the first medical research data set that is identified by the querying includes (a) the first medical research data and (b) second medical research data that is identified by the computing system as being relevant to the request based on the trained model, wherein the second medical research data was not requested by the first user in the request;
transmitting, by the computing system, the first medical research data set to the first user;
logging, by the computing system, the request and the first medical research data set into an audit log; and
repeating the receiving, the executing, the generating, the querying, and the transmitting in response to a second request from the first user for third medical research data to identify a second medical research data set that includes the third medical research data;
establishing a statistical correlation score between the first and second medical research data sets; and
upon the established correlation score exceeding a user-defined confidence interval, logging the established correlation score in the audit log and updating the trained model based on the established correlation score.
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Abstract
Embodiments of the present invention provide a computer-implemented method for allocating medical data access permissions using historical correlations. The method receives a request for medical research data from a user. The method executes natural language processing to interpret the received request. The method generates a database query based on a trained model to identify a medical research data set that is responsive to the request. The method queries one or more medical databases using the generated query to identify the medical research data set that is responsive to the request. The medical research data set that is identified includes the requested medical research data as well as additional medical research data that, although not requested by the user, is found to be relevant to the request based on the trained model. The method includes transmitting the medical research data set to the user.
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Citations
17 Claims
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1. A computer-implemented method for allocating medical data access permissions using historical correlations, the computer-implemented method comprising:
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receiving, by a computing system comprising one or more processors, a request for first medical research data from a first user; executing, by the computing system, natural language processing to interpret the request; generating, by the computing system, a database query based on a trained model to identify a first medical research data set that is responsive to the request, wherein the trained model takes into consideration (a) results of the natural language processing of the received request and (b) prior medical research data requests and responses that are stored in a historical database; querying, by the computing system, one or more medical databases using the query to identify the first medical research data set that is responsive to the request, wherein the first medical research data set that is identified by the querying includes (a) the first medical research data and (b) second medical research data that is identified by the computing system as being relevant to the request based on the trained model, wherein the second medical research data was not requested by the first user in the request; transmitting, by the computing system, the first medical research data set to the first user; logging, by the computing system, the request and the first medical research data set into an audit log; and repeating the receiving, the executing, the generating, the querying, and the transmitting in response to a second request from the first user for third medical research data to identify a second medical research data set that includes the third medical research data; establishing a statistical correlation score between the first and second medical research data sets; and upon the established correlation score exceeding a user-defined confidence interval, logging the established correlation score in the audit log and updating the trained model based on the established correlation score. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A system for allocating medical data access permissions using historical correlations, the system comprising one or more hardware processors configured to perform a method comprising:
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receiving, by the system, a request for first medical research data from a first user; executing, by the system, natural language processing to interpret the request; generating, by the system, a database query based on a trained model to identify a first medical research data set that is responsive to the request, wherein the trained model takes into consideration (a) results of the natural language processing of the received request and (b) prior medical research data requests and responses that are stored in a historical database; querying, by the system, one or more medical databases using the query to identify the first medical research data set that is responsive to the request, wherein the first medical research data set that is identified by the querying of the one or more medical databases includes (a) the first medical research data and (b) second medical research data that is identified by the system as being relevant to the request based on the trained model, wherein the second medical research data was not requested by the first user in the request; transmitting, by the system, the first medical research data set to the first user; logging, by the system, the request and the first medical research data set into an audit log; and repeating the receiving, the executing, the generating, the querying, and the transmitting in response to a second request from the first user for third medical research data to identify a second medical research data set that includes the third medical research data; establishing a statistical correlation score between the first and second medical research data sets; and upon the established correlation score exceeding a user-defined confidence interval, logging the established correlation score in the audit log and updating the trained model based on the established correlation score. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A computer program product for allocating medical data access permissions using historical correlations, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a system comprising one or more processors to cause the system to perform a method comprising:
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receiving, by the system, a request for first medical research data from a first user; executing, by the system, natural language processing to interpret the received request; generating, by the system, a database query based on a trained model to identify a first medical research data set that is responsive to the request, wherein the trained model takes into consideration (a) results of the natural language processing of the received request and (b) prior medical research data requests and responses that are stored in a historical database; querying, by the system, one or more medical databases using the generated query to identify the first medical research data set that is responsive to the request, wherein the first medical research data set that is identified by the querying of the one or more medical databases includes (a) the first medical research data and (b) second medical research data that is identified by the system as being relevant to the request based on the trained model, wherein the second medical research data was not requested by the first user in the request; transmitting, by the system, the first medical research data set to the first user; logging, by the system, the request and the first medical research data set into an audit log; and repeating the receiving, the executing, the generating, the querying, and the transmitting in response to a second request from the first user for third medical research data to identify a second medical research data set that includes the third medical research data; establishing a statistical correlation score between the first and second medical research data sets; and upon the established correlation score exceeding a user-defined confidence interval, logging the established correlation score in the audit log and updating the trained model based on the established correlation score. - View Dependent Claims (14, 15, 16, 17)
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Specification