Application US20190074073 AI Biotech/Diagnostics: Cardio

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Application US20190074073

Published 2019-03-07

Treatment Recommendations Based On Drug-to-drug Interactions

Cognitive medical treatment recommendation mechanisms are provided. The mechanisms ingest a corpus of medical treatment content that comprises drug-to-drug interaction information. The mechanisms generate a set of drug interaction insight data structures and an initial set of candidate treatments for a medical condition of a patient based on an analysis of an electronic medical record associated with the patient. The mechanisms rank candidate treatments in the initial set of candidate treatments based on the set of drug interaction insight data structures to generate a final set of candidate treatments, where the ranking reduces rankings of candidate treatments in which drug interactions are identified in the set of drug interaction insight data structures. The mechanisms output a treatment recommendation based on the final set of candidate treatments.

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4 Independent Claims

1-20. (canceled)
21. A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a cognitive medical treatment recommendation system, the method comprising: performing, by the cognitive medical treatment recommendation system, natural language processing on an electronic corpus of natural language electronic documents to extract drug-to-drug interaction data; ranking, by the cognitive medical treatment recommendation system, a set of candidate treatments for a medical condition of a patient based on an analysis of one or more electronic medical records (EMRs) associated with the patient and the extracted drug-to-drug interaction data, wherein ranking the set of candidate treatments comprises applying exclusionary weightings to confidence scores associated with candidate treatments that involve drugs that have drug-to-drug interactions with one or more other drugs associated with the patient as specified in the one or more EMRs; and outputting, by the cognitive medical treatment recommendation system, a treatment recommendation based on the ranked set of candidate treatments.
31. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a cognitive medical treatment recommendation system which operates to: perform natural language processing on an electronic corpus of natural language electronic documents to extract drug-to-drug interaction data; rank a set of candidate treatments for a medical condition of a patient based on an analysis of one or more electronic medical records (EMRs) associated with the patient and the extracted drug-to-drug interaction data, wherein ranking the set of candidate treatments comprises applying exclusionary weightings to confidence scores associated with candidate treatments that involve drugs that have drug-to-drug interactions with one or more other drugs associated with the patient as specified in the one or more EMRs; and output a treatment recommendation based on the ranked set of candidate treatments.
40. An apparatus comprising: at least one processor; and at least one memory coupled to the at least one processor, wherein the at least one memory comprises instructions which, when executed by the at least one processor, cause the at least one processor to: perform natural language processing on an electronic corpus of natural language electronic documents to extract drug-to-drug interaction data; rank a set of candidate treatments for a medical condition of a patient based on an analysis of one or more electronic medical records (EMRs) associated with the patient and the extracted drug-to-drug interaction data, wherein ranking the set of candidate treatments comprises applying exclusionary weightings to confidence scores associated with candidate treatments that involve drugs that have drug-to-drug interactions with one or more other drugs associated with the patient as specified in the one or more EMRs; and output a treatment recommendation based on the ranked set of candidate treatments.