UMP Institutional Repository

Soft Set-Based Decision Making For Patients Suspected Influenza-Like Illness

Herawan, Tutut (2010) Soft Set-Based Decision Making For Patients Suspected Influenza-Like Illness. International Journal of Modern Physics: Conference Series, 1 (1). pp. 1-5. ISSN 2010-1945

[img]
Preview
PDF
Full_Paper_ICMCB_CB_02_Soft_set-based_decision_making_for_patient_suspected_Influenza-Like_Illness-journal-.pdf

Download (139kB)

Abstract

In previous work, we presented an applicability of soft set theory for decision making of patients suspected influenza. The proposed technique is based on maximal supported objects by parameters. At this stage of the research, results are presented and discussed from a qualitative point of view against recent soft decision making techniques through an artificial dataset. In this paper, we present an extended application of our soft set-based decision making through a Boolean valued information system from a dataset of patients suspected ILI (Influenza-Like Illness). Using soft set theory and maximal symptoms co-occurences in patients, we explore how soft set-based decision making technique can be used to reduce the number of dispensable symptoms and further make a correct and fast decision. The result of this work can be used for recommendation of decision making based on the clusters decision captured. Finally, this technique may potentially contribute to lowering the complexity of medical decision making without loss of original information.

Item Type: Article
Uncontrolled Keywords: Decision making; Soft set theory; ILI dataset
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QC Physics
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Zairi Ibrahim
Date Deposited: 28 Dec 2011 02:25
Last Modified: 14 Sep 2017 05:39
URI: http://umpir.ump.edu.my/id/eprint/2065
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item