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

Pınar Kaya Aksoy; Fatih Erdemir; Deniz Kılınç; Orhan Er

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

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

References

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Details

Primary Language

English

Subjects

Clinical Sciences, Engineering

Journal Section

Research Article

Authors

Pınar Kaya Aksoy ^* This is me
0000-0003-2493-9955
Türkiye

Fatih Erdemir This is me
0000-0003-2493-9955
The Netherlands

Deniz Kılınç This is me
0000-0002-2336-8831
Türkiye

Orhan Er This is me
0000-0002-4732-9490
Türkiye

Publication Date

April 30, 2022

Submission Date

March 12, 2022

Acceptance Date

April 25, 2022

Published in Issue

Year 2022 Volume: 2 Number: 1

IZ

https://izlik.org/JA79YG62YA

Cite

RIS / Bibtex

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. https://izlik.org/JA79YG62YA

AMA

1.Kaya Aksoy P, Erdemir F, Kılınç D, Er O. A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis. AITA. 2022;2(1):14-26. https://izlik.org/JA79YG62YA

Chicago

Kaya Aksoy, Pınar, Fatih Erdemir, Deniz Kılınç, and Orhan Er. 2022. “A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis”. Artificial Intelligence Theory and Applications 2 (1): 14-26. https://izlik.org/JA79YG62YA.

EndNote

Kaya Aksoy P, Erdemir F, Kılınç D, Er O (April 1, 2022) A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis. Artificial Intelligence Theory and Applications 2 1 14–26.

IEEE

[1]P. Kaya Aksoy, F. Erdemir, D. Kılınç, and O. Er, “A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis”, AITA, vol. 2, no. 1, pp. 14–26, Apr. 2022, [Online]. Available: https://izlik.org/JA79YG62YA

ISNAD

Kaya Aksoy, Pınar - Erdemir, Fatih - Kılınç, Deniz - Er, Orhan. “A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis”. Artificial Intelligence Theory and Applications 2/1 (April 1, 2022): 14-26. https://izlik.org/JA79YG62YA.

JAMA

1.Kaya Aksoy P, Erdemir F, Kılınç D, Er O. A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis. AITA. 2022;2:14–26.

MLA

Kaya Aksoy, Pınar, et al. “A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis”. Artificial Intelligence Theory and Applications, vol. 2, no. 1, Apr. 2022, pp. 14-26, https://izlik.org/JA79YG62YA.

Vancouver

1.Pınar Kaya Aksoy, Fatih Erdemir, Deniz Kılınç, Orhan Er. A Decision Support System on Artificial Intelligence Based Early Diagnosis of Sepsis. AITA [Internet]. 2022 Apr. 1;2(1):14-26. Available from: https://izlik.org/JA79YG62YA