DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS

Ebru Pekel; Tuncay Özcan

DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS

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.

Keywords

References

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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Ebru Pekel This is me
0000-0001-7717-6790
Türkiye

Tuncay Özcan This is me
0000-0002-9520-2494
Türkiye

Publication Date

December 1, 2018

Submission Date

March 22, 2018

Acceptance Date

October 19, 2018

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Year 2018 Volume: 36 Number: 4

IZ

https://izlik.org/JA94CB47NW

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RIS / Bibtex

APA

Pekel, E., & Özcan, T. (2018). DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS. Sigma Journal of Engineering and Natural Sciences, 36(4), 1265-1282. https://izlik.org/JA94CB47NW

AMA

1.Pekel E, Özcan T. DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS. SIGMA. 2018;36(4):1265-1282. https://izlik.org/JA94CB47NW

Chicago

Pekel, Ebru, and Tuncay Özcan. 2018. “DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS”. Sigma Journal of Engineering and Natural Sciences 36 (4): 1265-82. https://izlik.org/JA94CB47NW.

EndNote

Pekel E, Özcan T (December 1, 2018) DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS. Sigma Journal of Engineering and Natural Sciences 36 4 1265–1282.

IEEE

[1]E. Pekel and T. Özcan, “DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS”, SIGMA, vol. 36, no. 4, pp. 1265–1282, Dec. 2018, [Online]. Available: https://izlik.org/JA94CB47NW

ISNAD

Pekel, Ebru - Özcan, Tuncay. “DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS”. Sigma Journal of Engineering and Natural Sciences 36/4 (December 1, 2018): 1265-1282. https://izlik.org/JA94CB47NW.

JAMA

1.Pekel E, Özcan T. DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS. SIGMA. 2018;36:1265–1282.

MLA

Pekel, Ebru, and Tuncay Özcan. “DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS”. Sigma Journal of Engineering and Natural Sciences, vol. 36, no. 4, Dec. 2018, pp. 1265-82, https://izlik.org/JA94CB47NW.

Vancouver

1.Ebru Pekel, Tuncay Özcan. DIAGNOSIS OF DIABETES MELLITUS USING STATISTICAL METHODS AND MACHINE LEARNING ALGORITHMS. SIGMA [Internet]. 2018 Dec. 1;36(4):1265-82. Available from: https://izlik.org/JA94CB47NW