Kronik Böbrek Hastalığının Erken Tanısı için Yeni Bir Klinik KararDestek Sistemi

Kronik böbrek hastalığı dünya çapında bir sağlık sorunudur. Erken tanı ve tedavi sayesinde bu hastalığın ilerlemesini yavaşlatmakveya durdurmak mümkün olmaktadır. Klinik karar destek sistemleri, tıp doktorlarına klinik karar verme görevlerinde yardımcı olmakamacıyla tasarlanan sağlık bilgi teknolojisi sistemleridir. Bu çalışmada kronik böbrek hastalığının erken tanısı için yeni bir klinikkarar destek sistemi önerilmiştir. Önerilen sistemin özellik çıkarma ve sınıflandırma aşamalarında sırasıyla temel bileşen analizi(principal component analysis-PCA) ve rastgele ormanlar (random forests-RF) teknikleri kullanılmıştır. Önerilen sisteminperformansı, altı farklı performans metriği ile klasik makine öğrenmesi algoritmaları ve literatürde daha önce yapılan çalışmalar ilekıyaslanmıştır. Test sonuçları, önerilen sistemin başarılı olduğunu ve kronik böbrek hastalığının erken tanısı için karar vermededoktorlara destek olabileceğini göstermektedir.

A New Clinical Decision Support System for Early Diagnosis of Chronic Kidney Disease

Chronic kidney disease is a worldwide health problem. It is possible to slow or stop the progression of this disease thanks to earlydiagnosis and treatment. Clinical decision support systems are health information technology systems designed to assist medicaldoctors in clinical decision making tasks. In this study, a new clinical decision support system is proposed for the early diagnosis ofchronic kidney disease. Principal component analysis (PCA) and random forests (RF) techniques are used in the feature extraction andclassification phases of the proposed system, respectively. The performance of the proposed system has been compared with classicalmachine learning algorithms and previous studies in the literature using six different performance metrics. The test results show thatthe proposed system is successful and can assist doctors in making decisions for early diagnosis of chronic kidney disease.

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