Abstract
This paper presents experiments with the application of rough set-based data mining methodology to discover predictive rules in small cell lung cancer patient data. The specific prediction targets are the occurrence of the spread of cancer to the brain and the prediction of patient survival time. The obtained results have been derived from patient data supplied by cancer researchers from the Allan Blair Cancer Center, Regina, Saskatchewan, Canada who also provided all the necessary background information and conducted medical evaluation of the results.
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© 2001 Springer-Verlag Berlin Heidelberg
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Aryeetey, K., Ziarko, W., Tai, P., Ago, C. (2001). Identification of Rules for Brain Metastases and Survival Time Prediction for Small Cell Lung Cancer Patients. In: Kłopotek, M.A., Michalewicz, M., Wierzchoń, S.T. (eds) Intelligent Information Systems 2001. Advances in Intelligent and Soft Computing, vol 10. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1813-0_1
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DOI: https://doi.org/10.1007/978-3-7908-1813-0_1
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1407-1
Online ISBN: 978-3-7908-1813-0
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