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

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

Pınar Kaya Aksoy Fatih Erdemir Deniz Kılınç Orhan Er

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.

Keywords

sepsis, early forecasting, artificial intelligence, decision support systems

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