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Journals / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2018 / Cilt: 36 - Sayı: 4

DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS

Ebru PEKEL
Tuncay ÖZCAN
Pages
1265–1282
Publication Date
2018-12-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study shows it is clear that the combination of different machine learning algorithms and optimization models can lead to more meaningful and powerful results.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The early diagnosis of the diabetes condition is crucial for cure process, because an early diagnosis provides the ease of treatment for the patient and the physician.
📊
Key Findings & Data:Also, this paper presents a literature review on the diagnosis diabetes up to the end of 2017.
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Conclusion & Impact:This study shows it is clear that the combination of different machine learning algorithms and optimization models can lead to more meaningful and powerful results.
🔬Design:Review & Systematic Survey
📍Scope:2017 Verileri
⚙️Variables:Classification · diabetes mellitus · machine learning

Abstract

The early diagnosis of the diabetes condition is crucial for cure process, because an early diagnosis provides the ease of treatment for the patient and the physician. At this point, statistical methods and data mining algorithms can provide important opportunities for early diagnosis of diabetes mellitus. In the literature, many studies have been published for solution of this problem. In this study, firstly, these studies are analyzed in detail and classified according to their methodologies and solution approaches. The main aim of this paper is to provide the comprehensive and detailed review of the diagnosis of diabetes by statistical methods and machine learning algorithms. Also, this paper presents a literature review on the diagnosis diabetes up to the end of 2017. It's identified over 425 papers, highly cited 100 ones are presented in detailed. This paper provides to guide future research and knowledge accumulation and creation of classification and prediction techniques in diagnosis of diabetes. This study shows it is clear that the combination of different machine learning algorithms and optimization models can lead to more meaningful and powerful results.

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Cite This Article

PEKEL, E., ÖZCAN, T. (2018). DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 36 - Sayı: 4, 1265–1282. https://ajindex.com/articles/419010

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