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Semantic Knowledge Representation

Diagram of semantic relationships
Project information

The Semantic Knowledge Representation project conducts basic research in symbolic natural language processing based on the UMLS knowledge sources. A core resource is the SemRep program, which extracts semantic predications from text. SemRep was originally developed for biomedical research. A general methodology is being developed for extending its domain, currently to influenza epidemic preparedness, health promotion, and health effects of climate change.                                          

The SKR project maintains a database of 60 million SemRep  predications extracted from all MEDLINE citations. This database supports the Semantic MEDLINE Web application, 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. Convenient access is also provided to additional relevant knowledge resources, such as Entrez Gene, the Genetics Home Reference, and UMLS Metathesaurus.                                               

SKR efforts support innovative infor­mation management applications in biomedicine, as well as basic research. The project team is using semantic predications to find publications that support critical questions used during the creation of clinical practice guidelines with support from the National Heart, Lung, Blood Institute. The Semantic MEDLINE technology was adapted to analyzing NIH grants as SPA  (Semantic Portfolio Analyst), with the support of the Division of Program Coordination, Planning, and Strategic Initiatives in the NIH Office of the Director.

Significant research in SKR is being devoted to developing and applying the literature-based discovery paradigm using semantic predications. One such project is investigating the physiology of sleep and associated pathologies, such as declining sleep quality in aging men, restless legs syndrome, and obstructive sleep apnea; another exploits predications and graph theory for automatic summarization of biomedical text. Further, the SKR team is collaborating with academic researchers in using semantic predications to help interpret the results of microarray experiments, to investigate advanced statistical methods for enhanced information management, and to address the information needs of clinicians at point-of-care.

Publications/Tools: 
Mrabet Y, Kilicoglu H, Roberts K, Demner-Fushman D. Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions. . J Am Med Inform Assoc. 2017 Feb 19. doi: 10.1093/jamia/ocw176. [Epub ahead of print]
Kilicoglu H. Inferring Implicit Causal Relationships in Biomedical Literature. Proc 15th Workshop on Biomedical Natural Language Processing. Pages 46-55. 2016.
Demner-Fushman D, Elhadad N. Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing. IMIA Yearbook of Medical Informatics 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.
Wei W, Marmor R, Singh S, Wang S, Demner-Fushman D, Kuo TT, Hsu CN, Ohno-Machado L. Finding Related Publications: Extending the Set of Terms Used to Assess Article Similarity. AMIA Jt Summits Transl Sci Proc. 2016 Jul 20;2016:225-34. eCollection 2016.
Roberts K, Demner-Fushman D. Interactive use of online health resources: a comparison of consumer and professional questions. J Am Med Inform Assoc. 2016 Jul;23(4):802-11. doi: 10.1093/jamia/ocw024. Epub 2016 May 4.
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.
Kilicoglu H, Rosemblat G, Cairelli M, Rindflesch TC. A Compositional Interpretation of Biomedical Event Factuality. Proc of the Second Workshop on Extra-Propositional Aspects of Meaning in Computational Semantics (ExProM 2015).

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