Title :
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
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;
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
DOI :
10.1109/ICCABS.2012.6182651
