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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2018

Open Access 01-12-2018 | Research article

A rank weighted classification for plasma proteomic profiles based on case-based reasoning

Author: Amy M. Kwon

Published in: BMC Medical Informatics and Decision Making | Issue 1/2018

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Abstract

Background

It is a challenge to precisely classify plasma proteomic profiles into their clinical status based solely on their patterns even though distinct patterns of plasma proteomic profiles are regarded as potential to be a biomarker because the profiles have large within-subject variances.

Methods

The present study proposes a rank-based weighted CBR classifier (RWCBR). We hypothesized that a CBR classifier is advantageous when individual patterns are specific and do not follow the general patterns like proteomic profiles, and robust feature weights can enhance the performance of the CBR classifier. To validate RWCBR, we conducted numerical experiments, which predict the clinical status of the 70 subjects using plasma proteomic profiles by comparing the performances to previous approaches.

Results

According to the numerical experiment, SVM maintained the highest minimum values of Precision and Recall, but RWCBR showed highest average value in all information indices, and it maintained the smallest standard deviation in F-1 score and G-measure.

Conclusions

RWCBR approach showed potential as a robust classifier in predicting the clinical status of the subjects for plasma proteomic profiles.
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Metadata
Title
A rank weighted classification for plasma proteomic profiles based on case-based reasoning
Author
Amy M. Kwon
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2018
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-018-0610-1

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