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A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis

Year 2022, Volume 2, Issue 1, 14 - 26, 30.04.2022

Abstract

Sepsis is the intense reaction of the immune system as a result of a severe infection in any part of the body and damages to organs and tissues. And this disease is commonly fatal and costly. In this study, we perform a comparative study for Sepsis prediction using machine learning algorithms from original laboratory findings. For this purpose, thirty-two different machine learning algorithms including different tructures as well as neural network classifiers are evaluated and compared. As a result of experimental studies, SVM (Cubic, Fine Gaussian), KNN (Fine, Weighted, Subspace), Trees (Weighted, Boosted, Bagged) and neural network-based classifiers have achieved a significant success rate in the diagnosis of Sepsis using the new dataset. Thus, it is concluded that it is appropriate to use machine learning algorithms to predict whether a Sepsis patient will be survived. This study has the potential to be used as a new supportive tool for doctors when predicting Sepsis.

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Details

Primary Language English
Subjects Engineering, Medicine
Journal Section Research Articles
Authors

Pınar KAYA AKSOY This is me (Primary Author)
IZMIR PROVINCIAL HEALTH DIRECTORATE
0000-0003-2493-9955
Türkiye


Fatih ERDEMİR This is me
Amatis Software Engineering
0000-0003-2493-9955
The Netherlands


Deniz KILINÇ This is me
IZMIR BAKIRCAY UNIVERSITY
0000-0002-2336-8831
Türkiye


Orhan ER This is me
IZMIR BAKIRCAY UNIVERSITY
0000-0002-4732-9490
Türkiye

Publication Date April 30, 2022
Published in Issue Year 2022, Volume 2, Issue 1

Cite

APA Kaya Aksoy, P. , Erdemir, F. , Kılınç, D. & Er, O. (2022). A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis . Artificial Intelligence Theory and Applications , 2 (1) , 14-26 . Retrieved from https://dergipark.org.tr/en/pub/aita/issue/70443/1136215