Abstract
The increasing availability of automated data collection tools, database technologies and Information and Communication Technologies in biomedicine and health care have led to huge amounts of biomedical and health-care data accumulated in several repositories. Unfortunately, the process of analysis of such data represents a complex task also because data volumes grow exponentially so manual analysis and interpretation become impractical. Fortunately, knowledge discovery in databases (KDD) and data mining (DM) are powerful tools available to medical and research people for help them in explore data and discover useful knowledge. To assess the spread of DM and KDD in biomedicine and health care, we designed and performed a search database of biomedical and health-care scientific literature, for the year interval 1997-2004, and analyzed the obtained results. There has been an increase of application of DM methods in literature of bio-medical informatics research most of which in bioinformatics and genomic area.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cios, K.J., Moore, G.W.: Uniqueness of medical data mining. Artif. Intell. Med. 26(1-2), 1–24 (2002)
Lucas, P.: Bayesian analysis, pattern analysis, and data mining in health care. Curr. Opin. Crit. Care. 10(5), 399–403 (2004)
Wilson, A.M., Thabane, L., Holbrook, A.: Application of data mining techniques in pharmacovigilance. Br. J. Clin. Pharmacol. 57(2), 127–134 (2004)
Lee, S.M., Abbott, P.A.: Bayesian networks for knowledge discovery in large datasets: basics for nurse researchers. J. Biomed. Inform. 36(4-5), 389–399 (2003)
Liu, H., Wong, L.: Data mining tools for biological sequences. J. Bioinform. Comput. Biol. 1(1), 139–167 (2003)
Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: The KDD process for extracting useful knowledge from volumes of data. Communication of ACM 39(11), 27–34 (1996)
Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery: An overview. AI Mag. 17(3), 37–54 (1996)
Weiss, S.M., Indurkhya, N.: Predictive data mining: a practical guide. Morgan Kaufmann Publishers, San Francisco (1997)
Han, J., Kamber, M.: Data mining: concepts and techniques. Morgan Kaufmann Publishers, San Francisco (2000)
National Library of Medicine. Entrez PubMed. Available at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi (Last access: June 1, 2005)
ISINET. The Journal Citation Report. Available at http://www.isinet.com/isi/products/citation/jcr (Last access: June 1, 2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bonacina, S., Masseroli, M., Pinciroli, F. (2005). Foreseeing Promising Bio-medical Findings for Effective Applications of Data Mining. In: Oliveira, J.L., Maojo, V., MartÃn-Sánchez, F., Pereira, A.S. (eds) Biological and Medical Data Analysis. ISBMDA 2005. Lecture Notes in Computer Science(), vol 3745. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573067_14
Download citation
DOI: https://doi.org/10.1007/11573067_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29674-4
Online ISBN: 978-3-540-31658-9
eBook Packages: Computer ScienceComputer Science (R0)Springer Nature Proceedings Computer Science
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.