@inproceedings{08576b048fec40b0bd9c7914cb76251b,
title = "Biomarker clustering of colorectal cancer data to complement clinical classification",
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.",
author = "Chris Roadknight and Uwe Aickelin and Alex Ladas and Daniele Soria and John Scholefield and Lindy Durrant",
year = "2012",
doi = "10.2139/ssrn.2828496",
language = "English",
isbn = "9781467307086",
series = "2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012",
publisher = "IEEE Computer Society",
pages = "187--191",
booktitle = "2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012",
address = "United States",
note = "2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012 ; Conference date: 09-09-2012 Through 12-09-2012",
}