DocumentCode
2378865
Title
Machine science in biomedicine: Practicalities, pitfalls and potential
Author
Kelsey, T.W. ; Wallace, W.H.B.
Author_Institution
Sch. of Comput. Sci., Univ. of St Andrews, St. Andrews, UK
fYear
2010
fDate
18-18 Dec. 2010
Firstpage
399
Lastpage
404
Abstract
Machine Science, or Data-driven Research, is a new and interesting scientific methodology that uses advanced computational techniques to identify, retrieve, classify and analyse data in order to generate hypotheses and develop models. In this paper we describe three recent biomedical Machine Science studies, and use these to assess the current state of the art with specific emphasis on data mining, data assessment, costs, limitations, skills and tool support.
Keywords
bioinformatics; data acquisition; data analysis; data mining; information retrieval; biomedical Machine Science; computational techniques; data analysis; data assessment; data classification; data identification; data mining; data retrieval; data-driven research; Biomedical computing; Data acquisition; Modeling; Text recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine Workshops (BIBMW), 2010 IEEE International Conference on
Conference_Location
Hong, Kong
Print_ISBN
978-1-4244-8303-7
Electronic_ISBN
978-1-4244-8304-4
Type
conf
DOI
10.1109/BIBMW.2010.5703835
Filename
5703835
Link To Document