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

Authors : Pınar KAYA AKSOY, Fatih ERDEMİR, Deniz KILINÇ, Orhan ER

Pages : 14-26

View : 122 | Download : 14

Publication Date : 2022-04-30

Article Type : Research Paper

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 insert ignore into journalissuearticles values(Cubic, Fine Gaussian);, KNN insert ignore into journalissuearticles values(Fine, Weighted, Subspace);, Trees insert ignore into journalissuearticles values(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.
Keywords : sepsis, early forecasting, artificial intelligence, decision support systems

ORIGINAL ARTICLE URL