Machine Science in Biomedicine: Practicalities, Pitfalls and Potential

Tom Kelsey, W H B Wallace

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationProceedings of the First Workshop on Knowledge Engineering, Discovery and Dissemination in Health (KEDDH10)
Subtitle of host publicationProc. KEDDH10
PublisherIEEE Computer Society
Pages117-122
Number of pages6
ISBN (Print)978-1-4244-8302-0
Publication statusPublished - 18 Dec 2010

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