Biomarker clustering of colorectal cancer data to complement clinical classification

Chris Roadknight, Uwe Aickelin, Alex Ladas, Daniele Soria, John Scholefield, Lindy Durrant

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012
PublisherIEEE Computer Society
Pages187-191
Number of pages5
ISBN (Print)9781467307086
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012 - Wroclaw, Poland
Duration: 9 Sept 201212 Sept 2012

Publication series

Name2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012

Conference

Conference2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012
Country/TerritoryPoland
CityWroclaw
Period9/09/1212/09/12

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems

Fingerprint

Dive into the research topics of 'Biomarker clustering of colorectal cancer data to complement clinical classification'. Together they form a unique fingerprint.

Cite this