International Business Machines Corporation

Michael Britt

Richard Joseph Stevens

Adam Charles Lange-Pearson

Thomas P Pitzen

Fernando Jose Suarez Saiz

Corey Sanders

Christopher Thomas Gloe

Chris M Mwarabu

Techniques for cognitively interpreting comparative statements are provided. A corpus of documents associated with treatment of a first medical disorder is received. Relative efficacies for a plurality of therapies are determined by, for at least a first respective document in the corpus of documents, identifying and extracting, using one or more natural language processing techniques, a conclusion specified within natural language text of the respective document, where the conclusion includes a comparison between two or more therapies of the plurality of therapies, determining a sentiment of the extracted conclusion, with respect to at least one therapy of the plurality of therapies, and identifying one or more cohorts of patients that are associated with the conclusion. A knowledge graph is generated based on the relative efficacies.

Extraction, representation, and cognitive interpretation of medically relevant evidence

A method of searching a database of medical research for documentation in support of a specific treatment for a patient, the method including: identifying a medical condition; identifying attributes of the patient; searching the database for treatment regimens for the medical condition; scoring identified treatment regimens based on similarity of the attributes of the patient to cohorts treated with the treatment regimens and outcomes; and providing a recommendation for a treatment regimen for the patient based on the attributes of the patient.

Identifying a treatment regimen based on patient characteristics

A method, computer program product, and computing system device for receiving, at a computing device, a plurality of candidate therapy options, a corpus of therapy data, and a set of therapy recipient cohorts. At least a portion of therapy data may be filtered from the corpus of therapy data based upon, at least in part, the plurality of candidate therapy options and the set of therapy recipient cohorts. A graph may be generated to include a plurality of nodes representative of the plurality of candidate therapy options and a plurality of connections between the plurality of nodes indicating a sentiment factor with respect to the plurality of candidate therapy options based upon, at least in part, the at least a portion of therapy data filtered from the corpus of therapy data. Using the graph, a ranked list of the plurality of candidate therapy options may be generated.

Therapy recommendation

Methods to provide selective supporting evidence processing by applying a first machine learning (ML) model to a first candidate answer to generate a first confidence score that does not consider supporting evidence for the first candidate answer, determining, from a second ML model, an expected contribution of processing supporting evidence for the first candidate answer, and upon determining that the expected contribution does not exceed a specified threshold, skipping supporting evidence processing for the first candidate answer.

Avoiding supporting evidence processing when evidence scoring does not affect final ranking of a candidate answer

Systems and computer program products to provide selective supporting evidence processing by applying a first machine learning (ML) model to a first candidate answer to generate a first confidence score that does not consider supporting evidence for the first candidate answer, determining, from a second ML model, an expected contribution of processing supporting evidence for the first candidate answer, and upon determining that the expected contribution does not exceed a specified threshold, skipping supporting evidence processing for the first candidate answer.

Systems, methods, and computer program products to perform an operation comprising receiving a case, generating a set of candidate answers for the case, excluding a first candidate answer from the set of candidate answers upon determining that a first attribute in the case precludes returning the first candidate answer as a valid response to the case, and processing supporting evidence for the remaining candidate answers in the set of candidate answers.

Avoidance of supporting evidence processing based on key attribute predictors

Systems, methods, and computer program products to perform an operation comprising receiving a case from a user, determining a level of sophistication of the user, determining a level of sophistication associated with each of a plurality of items of supporting evidence in a corpus of information, selecting a subset of the plurality of items of supporting evidence based on the determined levels of sophistication, and returning the selected subset to the user as part of a response to the case.

Tailored supporting evidence

In an embodiment, a guest operating system receives first host network information that identifies a host virtual network adapter. The first host network information uniquely identifies the host virtual network adapter. The guest operating system sends a first frame that comprises the first host network information to a guest virtual network adapter. The guest virtual network adapter sends the first frame to the host virtual network adapter. The guest operating system receives second host network information that identifies the host virtual network adapter. The second host network information uniquely identifies the host virtual network adapter. The guest operating system sends a second frame that comprises the second host network information to the guest virtual network adapter. The guest virtual network adapter sends the second frame to the host virtual network adapter identified by the second host network information in the second frame.

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Rochester, MN, United States of America

Michael Britt