Correlation-based cluster-space transform for major adverse cardiac event prediction
2010 (English)In: IEEE International Conference on Systems Man and Cybernetics (SMC), 2010, IEEE , 2010, 2003-2007 p.Conference paper (Refereed)Text
This paper investigates the affect of variation of patterns in protein profiles to the identification of disease-specific biomarkers. A correlation-based cluster-space transform is applied to mass spectral data for predicting major adverse cardiac events (MACE). Training and testing data are transformed into cluster spaces by correlation distance based clustering, respectively. Data in the testing cluster that falls into a pair of training clusters is classified by a supervised classifier. Experiment results have shown that proteomic spectra of MACE which vary with certain patterns could be separated by the correlation-based clustering. The cluster-space transform allows better classification accuracy than single-clustered class method for separating disease and healthy samples.
Place, publisher, year, edition, pages
IEEE , 2010. 2003-2007 p.
classification; clustering; major adverse cardiac events; mass spectrometry
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-125014DOI: 10.1109/ICSMC.2010.5641728OAI: oai:DiVA.org:liu-125014DiVA: diva2:902785
IEEE International Conference on Systems Man and Cybernetics (SMC), Istanbul, Turkey, 10-13 Oct. 2010