Biomarker CA125 Feature Engineering and Class Imbalance Learning Improves Ovarian Cancer Prediction

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27032

Title:	Biomarker CA125 Feature Engineering and Class Imbalance Learning Improves Ovarian Cancer Prediction
Authors:	Yang, X Khushi, M Shaukat, K
Keywords:	machine learning;feature engineering;class imbalance;ovarian cancer
Issue Date:	16-Dec-2020
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Citation:	Yang, X., Khushi, M. and Shaukat, K. (2020) 'Biomarker CA125 Feature Engineering and Class Imbalance Learning Improves Ovarian Cancer Prediction', 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2020. Gold Coast, Australia, 16-18 December, pp. 1 - 6. doi: 10.1109/CSDE50874.2020.9411607.
URI:	https://bura.brunel.ac.uk/handle/2438/27032
DOI:	https://doi.org/10.1109/CSDE50874.2020.9411607
ISBN:	978-1-6654-1974-1 (ebk) 978-1-6654-2991-7 (PoD)
Other Identifiers:	ORCID iD: Matloob Khushi https://orcid.org/0000-0001-7792-2327
Appears in Collections:	Dept of Computer Science Research Papers

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