Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests

Özgül Özer; Nazlı Arda

doi:10.35377/saucis...1094043

EN

Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests

Abstract

Celiac disease; is an autoimmune digestive system disease characterized by chronic intestinal inflammation and villus antrophy and triggered by dietary gluten genetically susceptible individuals. Diagnosis is based on serological tests and small bowel biopsy. Because of the diversity in the clinical features of the disease, various patient profile and the non-standardized serological tests, it is difficult to diagnose the celiac disease. Sensitivity, specificity, positive and negative predictive values are important parameters for the accuracy of the tests and they are missing in some clinicial studies. It is difficult do standardize the tests with these missing values for clinicians. The aim of this study is to train different machine learning algorithms and to test their performance in prediction of the diagnostic accurary parameters of celiac serological tests. Decision trees are effective machine learning algorithms for predicting potential covariates with %88,7 accuracy.

Keywords

References

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Authors

Özgül Özer ^*
0000-0003-4265-3563
Türkiye

Nazlı Arda
0000-0002-1043-5652
Türkiye

Publication Date

April 30, 2022

Submission Date

March 27, 2022

Acceptance Date

April 4, 2022

Published in Issue

Year 1970 Volume: 5 Number: 1

DOI

https://doi.org/10.35377/saucis...1094043

IZ

https://izlik.org/JA59XL83LM

Cite

RIS / Bibtex

APA

Özer, Ö., & Arda, N. (2022). Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests. Sakarya University Journal of Computer and Information Sciences, 5(1), 84-89. https://doi.org/10.35377/saucis...1094043

AMA

1.Özer Ö, Arda N. Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests. SAUCIS. 2022;5(1):84-89. doi:10.35377/saucis.1094043

Chicago

Özer, Özgül, and Nazlı Arda. 2022. “Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests”. Sakarya University Journal of Computer and Information Sciences 5 (1): 84-89. https://doi.org/10.35377/saucis. 1094043.

EndNote

Özer Ö, Arda N (April 1, 2022) Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests. Sakarya University Journal of Computer and Information Sciences 5 1 84–89.

IEEE

[1]Ö. Özer and N. Arda, “Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests”, SAUCIS, vol. 5, no. 1, pp. 84–89, Apr. 2022, doi: 10.35377/saucis...1094043.

ISNAD

Özer, Özgül - Arda, Nazlı. “Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests”. Sakarya University Journal of Computer and Information Sciences 5/1 (April 1, 2022): 84-89. https://doi.org/10.35377/saucis. 1094043.

JAMA

1.Özer Ö, Arda N. Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests. SAUCIS. 2022;5:84–89.

MLA

Özer, Özgül, and Nazlı Arda. “Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests”. Sakarya University Journal of Computer and Information Sciences, vol. 5, no. 1, Apr. 2022, pp. 84-89, doi:10.35377/saucis. 1094043.

Vancouver

1.Özgül Özer, Nazlı Arda. Comparision of Different Machine Learning Algorithms to Predict the Diagnostic Accuracy Parameters of Celiac Serological Tests. SAUCIS. 2022 Apr. 1;5(1):84-9. doi:10.35377/saucis. 1094043