Cognitive framework to detect adverse events in free-form text
AssigneeInternational Business Machines Corporation
InventorsMeenakshi NAGARAJAN, Cartic RAMAKRISHNAN, Sheng Hua BAO, Nakul CHAKRAPANI
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Abstract
Performing an operation comprising extracting, from an input comprising unstructured electronic text, a plurality of feature values for a plurality of features defined in a feature vector, identifying, based on a machine learning (ML) model applied to the plurality of feature values, a portion of the electronic text corresponding to an adverse event, and annotating the portion of the electronic text with an indication of the identified adverse event.
Claims20
A computer-implemented method, comprising:
- extracting, from an input comprising unstructured electronic text, a plurality of feature values for a plurality of features defined in a feature vector;
- identifying, based on a machine learning (ML) model applied to the plurality of feature values, a portion of the electronic text corresponding to an adverse event;
- and
- annotating, by a computer processor, the portion of the electronic text with an indication of the identified adverse event.
A system, comprising:
- a processor;
- and
- a memory containing a program which when executed by the processor performs an operation comprising:
- extracting, from an input comprising unstructured electronic text, a plurality of feature values for a plurality of features defined in a feature vector;
- identifying, based on a machine learning (ML) model applied to the plurality of feature values, a portion of the electronic text corresponding to an adverse event;
- and
- annotating the portion of the electronic text with an indication of the identified adverse event
A computer program product, comprising:
- a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by a processor to perform an operation comprising:
- extracting, from an input comprising unstructured electronic text, a plurality of feature values for a plurality of features defined in a feature vector;
- identifying, based on a machine learning (ML) model applied to the plurality of feature values, a portion of the electronic text corresponding to an adverse event;
- and
- annotating, by a computer processor, the portion of the electronic text with an indication of the identified adverse event.
Dependencies are inferred from the claim text.