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Semantic Knowledge Representation

Diagram of semantic relationships
Project information
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Note: this web page will be archived on or around October 1 2019 and will be part of the NLM Lister Hill National Center for Biomedical Communications archive collection.

Semantic Knowledge Representation

In support of innovative information management applications in biomedicine as well as basic research, the Semantic Knowledge Representation project (SKR) efforts use symbolic natural language processing based on the UMLS knowledge sources. SKR research examples include developing and applying the literature-based discovery paradigm using semantic predications. One such project looked into the physiology of sleep and associated pathologies, such as declining sleep quality in aging men, restless legs syndrome, and obstructive sleep apnea; another project exploited predications and graph theory for automatic summarization of biomedical text.

SemRep

A core SKR resource is the SemRep program, which extracts semantic predications from text. Originally developed for biomedical research, SemRep was subsequently extended to genetic etiology and pharmacogenomics. Then, through a general methodology based on ontology and thesauri development, SemRep's application was extended to other fields, such as influenza epidemic preparedness and health promotion.  By applying natural language processing techniques, our research can better inform patients, health care providers, researchers, and the general public.

SemMedDB

The SKR project maintains SemMedDB, a repository of 96.3 million SemRep predications (subject-predicate-object triples) extracted our semantic interpreter SemRep from all MEDLINE citations up to Dec. 2018. This database supports the Semantic MEDLINE web application (SemMed), which integrates PubMed searching, SemRep predications, automatic summarization, and data visualization. The application is intended to help users manage the results of PubMed searches. Output is visualized as an informative graph with links to the original MEDLINE citations.

Downloads related to SemRep, SemMedDB, and SKR are available from our Access to SemRep/SemMedDB/SKR Resources page.

Publications/Tools: 
Kilicoglu H, Rosemblat G, Malicki M, Ter Riet G. Automatic recognition of self-acknowledged limitations in clinical research literature. J Am Med Inform Assoc. 2018 Jul 1;25(7):855-861. doi: 10.1093/jamia/ocy038.
Blake C, Rindflesch TC. Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases. J Biomed Inform. 2017 Aug;72:120-131. doi: 10.1016/j.jbi.2017.07.001. Epub 2017 Jul 4.
Kilicoglu H, Rosemblat G, Rindflesch TC. Assigning factuality values to semantic relations extracted from biomedical research literature. PLoS One. 2017 Jul 5;12(7):e0179926. doi: 10.1371/journal.pone.0179926. eCollection 2017.
Rindflesch TC, Blake CL, Fiszman M, Kilicoglu H, Rosemblat G, Schneider J, Zeiss CJ. Informatics Support for Basic Research in Biomedicine. ILAR J. 2017 Jul 1;58(1):80-89. doi: 10.1093/ilar/ilx004.
Kilicoglu H. Biomedical text mining for research rigor and integrity: tasks, challenges, directions. Brief Bioinform. 2017 Jun 13. doi: 10.1093/bib/bbx057.
Kilicoglu H. Inferring Implicit Causal Relationships in Biomedical Literature. Proc 15th Workshop on Biomedical Natural Language Processing. Pages 46-55. 2016.
Hristovski D, Kastrin A, Dinevski D, Burgun A, Ziberna L, Rindflesch TC. Using Literature-Based Discovery to Explain Adverse Drug Effects. J Med Syst. 2016 Aug;40(8):185. doi: 10.1007/s10916-016-0544-z. Epub 2016 Jun 18.
Kilicoglu H, Rosemblat G, Fiszman M, Rindflesch TC. Sortal anaphora resolution to enhance relation extraction from biomedical literature. BMC Bioinformatics. 2016 Apr 14;17:163. doi: 10.1186/s12859-016-1009-6.
Workman TE, Fiszman M, Cairelli MJ, Nahl D, Rindflesch TC. Spark, an application based on Serendipitous Knowledge Discovery. J Biomed Inform. 2016 Apr;60:23-37. doi: 10.1016/j.jbi.2015.12.014. Epub 2015 Dec 28.
Morid MA, Fiszman M, Raja K, Jonnalagadda SR, Del Fiol G. Classification of clinically useful sentences in clinical evidence resources. J Biomed Inform. 2016 Apr;60:14-22. doi: 10.1016/j.jbi.2016.01.003. Epub 2016 Jan 13.

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