Acute Cystitis and Acute Nephritis Prediction Using Machine Learning Techniques

§ PSGR Krishnammal College for Women, Coimbatore

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Acute Cystitis and Acute Nephritis Prediction Using Machine Learning Techniques

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Abstract

Urinary System includes kidneys, bladder, ureters and urethra. This is the major system involves electrolyte balance of the body and filters the blood and excretes the waste products in the form urine. Even the small disturbance in the renal function will step in a disasters manifestation. Among them we are considering the two diseases that affect the system are acute cystitis and acute nephritis. This paper presents the implementation of three supervised learning algorithms, ZeroR, J48 and Naive Bayes in WEKA environment. The classification models were trained using the data collected from 120 patients. The trained models were then used for predicting the acute cystitis or acute nephritis of the patients. The prediction accuracy of the classifiers was evaluated using 10-fold cross validation and the results were compared.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. R. Kowsalya. 1970. "Acute Cystitis and Acute Nephritis Prediction Using Machine Learning Techniques". Global Journal of Computer Science and Technology GJCST Volume 10 (GJCST Volume 10 Issue 8).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
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v1.2

Issue date
September 20, 2010

Language
English
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Acute Cystitis and Acute Nephritis Prediction Using Machine Learning Techniques

Dr. Kowsalya
Dr. Kowsalya PSGR Krishnammal College for Women, Coimbatore
Dr. Kowsalya
Dr. Kowsalya
Dr. Kowsalya
Dr. Kowsalya