Semantic Modeling of Cohort Descriptions in Research Studies

Author

Shruthi ChariRukmal WeerawaranaOshani SeneviratneJamie McCuskerDeborah L. McGuinnessAmar Das

Date

October 29, 2018

Organizations

Rensselaer Polytechnic InstituteIBM Research

Work Experience

Research Fellow

The paper proposes a new approach for augmenting clinical guideline recommendations with information about patient populations from cited literature. This approach is based on techniques from the fields of information extraction and knowledge representation, and involves the development of a Cohort Ontology to model patient groups and interventions mentioned in cited publications. The ultimate goal of this approach is to assist physicians and computers in suggesting recommendations for complex patients using cohort alignment.

Semantic Modeling of Cohort Descriptions in Research Studies

Recommendations in ADA's Standards of Medical Care in Diabetes guideline are supported by findings from scientific publications (primarily clinical trials and case studies). We propose an approach rooted in Information Extraction and Knowledge Representation techniques to augment guideline representations with population descriptions from cited literature.

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