Roadknight, Chris, Aickelin, Uwe, Ladas, Alex, Soria, Daniele, Scholefield, John, Durrant, Lindy (2012) Biomarker clustering of colorectal cancer data to complement clinical classification. In: 2012 Federated Conference on Computer Science and Information Systems (FedCSIS). . pp. 187-191. IEEE ISBN 978-1-4673-0708-6. (doi:10.2139/ssrn.2828496) (KAR id:98899)
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Official URL: https://doi.org/10.2139/ssrn.2828496 |
Abstract
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and post-operative survival. Attempts are made to cluster this dataset and important subsets of it in an effort to characterize the data and validate existing standards for tumour classification. It is apparent from optimal clustering that existing tumour classification is largely unrelated to immunological factors within a patient and that there may be scope for re-evaluating treatment options and survival estimates based on a combination of tumour physiology and patient histochemistry. © 2012 Polish Info Processing Socit.
Item Type: | Conference or workshop item (Paper) |
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DOI/Identification number: | 10.2139/ssrn.2828496 |
Additional information: | cited By 3 |
Uncontrolled keywords: | Tumors, Cancer, Immune system, Indexes, Educational institutions, Measurement |
Subjects: | Q Science > QA Mathematics (inc Computing science) |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Daniel Soria |
Date Deposited: | 08 Dec 2022 10:27 UTC |
Last Modified: | 05 Nov 2024 13:04 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/98899 (The current URI for this page, for reference purposes) |
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