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
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;
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
DOI :
10.1109/BIBMW.2010.5703835
