Abstract

This work introduces a fuzzy multi-objective function for performance evaluation in feature selection for a knowledge based medical classification task. Fuzzy optimization was used to combine the sensitivity, specificity, and percentage of correct classifications as objectives, and assign flexible goals to strengthen the sensitivity. Using the same soft computing methods and publicly available septic shock database as in Fialho et al. (2010), an increase in sensitivity of 30% was achieved while maintaining the percentage of correct classifications. Feature subsets selected were different from those previously published, lending insight into factors more integrally connected to what causes risk of death for patients.

Date

2011

Authors

Abigail L Horn, Federico Cismondi, André S Fialho, Susana M Vieira, Joao MC Sousa, Shane Reti, Michael Howell, Stan Finkelstein

Journal

IFAC Proceedings Volumes

Volume

44

Issue

1

Pages

14042-14047

Publisher

Elsevier