@inproceedings { , 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 postoperative 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.}, conference = {Federated Conference on Computer Science and Information Systems (FedCSIS)}, organization = {Wroc?aw, Poland}, publicationstatus = {Unpublished}, url = {https://nottingham-repository.worktribe.com/output/1009235}, author = {Roadknight, Chris and Aickelin, Uwe and Ladas, Alex and Soria, Daniele and Scholefield, John and Durrant, Lindy} }