DocumentCode :
1787396
Title :
Representing Evidence from Biomedical Literature for Clinical Decision Support: Challenges on Semantic Computing and Biomedicine
Author :
Hsu, Wei-Chou
Author_Institution :
Dept. of Radiol. Sci., Med. Imaging Inf. Group, Univ. of California, Los Angeles, Los Angeles, CA, USA
fYear :
2014
fDate :
16-18 June 2014
Firstpage :
1
Lastpage :
2
Abstract :
The rate at which biomedical literature is being published is quickly outpacing our ability to effectively leverage this information for evidence-based medicine. While papers are readily searchable through databases such as Pub Med, clinicians are often left with the time-consuming task of finding, assessing, interpreting, and applying this information. Tools that structure evidence from published papers using a standardized data model and provide an intuitive query interface for exploring documented biomedical entities would be valuable in utilizing this information as part of the clinical decision making process. This talk presents efforts towards developing computational tools and a representation for modeling and relating evidence from multiple clinical trial reports for lung cancer. Challenges related to representing this information in a machine-interpretable manner, assessing study quality, and handling conflicting evidence are described. I discuss the development of two tools: 1) an annotator tool used to extract information from papers, mapping it to concepts in an ontology-based representation and 2) a visualization that summarizes information about a single paper based on information captured in the model. Using lung cancer as a driving example, I demonstrate how these tools help users apply information reported in literature towards individually tailored medicine.
Keywords :
cancer; data visualisation; decision support systems; medical information systems; ontologies (artificial intelligence); query processing; PubMed database; annotator tool; biomedical literature; biomedicine; clinical decision making process; clinical decision support; evidence-based medicine; information application; information assessment; information interpretation; information representation; lung cancer; machine-interpretable information; ontology-based representation; query interface; semantic computing; visualization; Biomedical imaging; Cancer; Clinical trials; Diseases; Lungs; Ontologies; biomedical ontologies; evidence-based medicine; knowledge representation; literature based discovery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Computing (ICSC), 2014 IEEE International Conference on
Conference_Location :
Newport Beach, CA
Print_ISBN :
978-1-4799-4002-8
Type :
conf
DOI :
10.1109/ICSC.2014.67
Filename :
6881992
Link To Document :
بازگشت