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EpiphaNet: An Interactive Tool to Support Biomedical Discoveries.

Cohen T, Whitfield GK, Schvaneveldt RW, Mukund K, Rindflesch T - J Biomed Discov Collab (2010)

Bottom Line: In this paper, we discuss the theoretical and methodological foundations of the system, and evaluate the utility of the models that underlie it for literature-based discovery.In addition, we present a summary of results drawn from a qualitative analysis of over six hours of interaction with the system by basic medical scientists.This tool is available online, providing biomedical scientists with the opportunity to identify and explore associations of interest to them.

View Article: PubMed Central - PubMed

Affiliation: University of Texas Health Science Center. treversec@gmail.com.

ABSTRACT

Unlabelled: Background. EpiphaNet is an interactive knowledge discovery system which enables researchers to explore visually sets of relations extracted from MEDLINE using a combination of language processing techniques. In this paper, we discuss the theoretical and methodological foundations of the system, and evaluate the utility of the models that underlie it for literature-based discovery. In addition, we present a summary of results drawn from a qualitative analysis of over six hours of interaction with the system by basic medical scientists.

Results: The system is able to simulate open and closed discovery, and is shown to generate associations that are both surprising and interesting within the area of expertise of the researchers concerned.

Conclusions: EpiphaNet provides an interactive visual representation of associations between concepts, which is derived from distributional statistics drawn from across the spectrum of biomedical citations in MEDLINE. This tool is available online, providing biomedical scientists with the opportunity to identify and explore associations of interest to them.

No MeSH data available.


Open and closed LBD using EpiphaNet.  In both cases, the starting point or points for the discovery process have thick borders, and the endpoint is surrounded by a starburst.
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figure6: Open and closed LBD using EpiphaNet. In both cases, the starting point or points for the discovery process have thick borders, and the endpoint is surrounded by a starburst.


EpiphaNet: An Interactive Tool to Support Biomedical Discoveries.

Cohen T, Whitfield GK, Schvaneveldt RW, Mukund K, Rindflesch T - J Biomed Discov Collab (2010)

Open and closed LBD using EpiphaNet.  In both cases, the starting point or points for the discovery process have thick borders, and the endpoint is surrounded by a starburst.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2990276&req=5

figure6: Open and closed LBD using EpiphaNet. In both cases, the starting point or points for the discovery process have thick borders, and the endpoint is surrounded by a starburst.
Bottom Line: In this paper, we discuss the theoretical and methodological foundations of the system, and evaluate the utility of the models that underlie it for literature-based discovery.In addition, we present a summary of results drawn from a qualitative analysis of over six hours of interaction with the system by basic medical scientists.This tool is available online, providing biomedical scientists with the opportunity to identify and explore associations of interest to them.

View Article: PubMed Central - PubMed

Affiliation: University of Texas Health Science Center. treversec@gmail.com.

ABSTRACT

Unlabelled: Background. EpiphaNet is an interactive knowledge discovery system which enables researchers to explore visually sets of relations extracted from MEDLINE using a combination of language processing techniques. In this paper, we discuss the theoretical and methodological foundations of the system, and evaluate the utility of the models that underlie it for literature-based discovery. In addition, we present a summary of results drawn from a qualitative analysis of over six hours of interaction with the system by basic medical scientists.

Results: The system is able to simulate open and closed discovery, and is shown to generate associations that are both surprising and interesting within the area of expertise of the researchers concerned.

Conclusions: EpiphaNet provides an interactive visual representation of associations between concepts, which is derived from distributional statistics drawn from across the spectrum of biomedical citations in MEDLINE. This tool is available online, providing biomedical scientists with the opportunity to identify and explore associations of interest to them.

No MeSH data available.