Identifying cancer biomarkers by knowledge discovery from medical literature

Author

Dawoud, Khaled ; Qabaja, Ala ; Gao, Shang ; Alhajj, Reda ; Rokne, Jon

Author_Institution

Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada

fYear

2012

fDate

23-25 Feb. 2012

Firstpage

1

Lastpage

1

Abstract

The importance of extracting valuable information from published articles has been well recognized by the research community. The literature is growing exponentially bringing the need for automated extraction of domain specific information. The outcome could serve a wide range of applications. We present MedBuilder as a tool capable of extracting relationships and association links from row data format, to produce an association network. It is a reliable system and has high flexibility to be used in wide range of areas. We test MedBuilder on biomedical field by extracting pubmed abstracts related to breast cancers.

Keywords

biological organs; cancer; data mining; gynaecology; medical computing; association network; automated extraction; breast cancers; domain specific information; identifying cancer biomarkers; knowledge discovery; medbuilder; medical literature; reliable system; row data format; Abstracts; Breast cancer; Data mining; Databases; Diseases; Feature extraction; Frequency measurement; information extraction; network; text mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Advances in Bio and Medical Sciences (ICCABS), 2012 IEEE 2nd International Conference on

Conference_Location

Las Vegas, NV

Print_ISBN

978-1-4673-1320-9

Electronic_ISBN

978-1-4673-1319-3

Type

conf

DOI

10.1109/ICCABS.2012.6182651

Filename

6182651