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Diagnosing Diabetes with Machine Learning Techiques

Year 2022, Volume 9, Issue 1, 9 - 18, 30.03.2022
https://doi.org/10.17350/HJSE19030000250

Abstract

The rate of diabetes is rapidly increasing worldwide. Early detection of diabetes can help prevent or delay the onset of diabetes by initiating lifestyle changes and taking appropriate preventive measures. Until now, prediabetes and type 2 diabetes have proved to be early detection problems. There is a need for easy, rapid, and accurate diagnostic tools for the early diagnosis of diabetes in this context. Machine learning algorithms can help diagnose diseases early. Numerous studies are being conducted to improve the speed, performance, reliability, and accuracy of diagnosing with these methods for a particular disease. This study aims to predict whether a patient has diabetes based on diagnostic measurements in a dataset from the National Institute of Diabetes and Digestive and Kidney Diseases. Eight different variables belonging to the patients were selected as the input variable, and it was estimated whether the patient had diabetes or not. Of the 768 records examined, 500 (65.1%) were healthy, and 268 (34.9%) had diabetes. Ten different machine learning algorithms have been applied to predict diabetic status. The most successful method was the Random Forest algorithm with 90.1% accuracy. Accuracy percentages of other algorithms are also between 89% and 81%. This study describes a highly accurate machine learning prediction tool for finding patients with diabetes. The model identified in the study may be helpful for early diabetes diagnosis.

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Year 2022, Volume 9, Issue 1, 9 - 18, 30.03.2022
https://doi.org/10.17350/HJSE19030000250

Abstract

References

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Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Ömer Faruk AKMEŞE (Primary Author)
HİTİT ÜNİVERSİTESİ
0000-0002-5877-0177
Türkiye

Publication Date March 30, 2022
Application Date September 12, 2021
Acceptance Date January 10, 2022
Published in Issue Year 2022, Volume 9, Issue 1

Cite

Bibtex @research article { hjse994520, journal = {Hittite Journal of Science and Engineering}, issn = {}, eissn = {2148-4171}, address = {Hitit Üniversitesi Mühendislik Fakültesi Kuzey Kampüsü Çevre Yolu Bulvarı 19030 Çorum / TÜRKİYE}, publisher = {Hitit University}, year = {2022}, volume = {9}, pages = {9 - 18}, doi = {10.17350/HJSE19030000250}, title = {Diagnosing Diabetes with Machine Learning Techiques}, key = {cite}, author = {Akmeşe, Ömer Faruk} }
APA Akmeşe, Ö. F. (2022). Diagnosing Diabetes with Machine Learning Techiques . Hittite Journal of Science and Engineering , 9 (1) , 9-18 . DOI: 10.17350/HJSE19030000250
MLA Akmeşe, Ö. F. "Diagnosing Diabetes with Machine Learning Techiques" . Hittite Journal of Science and Engineering 9 (2022 ): 9-18 <https://dergipark.org.tr/en/pub/hjse/issue/69208/994520>
Chicago Akmeşe, Ö. F. "Diagnosing Diabetes with Machine Learning Techiques". Hittite Journal of Science and Engineering 9 (2022 ): 9-18
RIS TY - JOUR T1 - Diagnosing Diabetes with Machine Learning Techiques AU - Ömer Faruk Akmeşe Y1 - 2022 PY - 2022 N1 - doi: 10.17350/HJSE19030000250 DO - 10.17350/HJSE19030000250 T2 - Hittite Journal of Science and Engineering JF - Journal JO - JOR SP - 9 EP - 18 VL - 9 IS - 1 SN - -2148-4171 M3 - doi: 10.17350/HJSE19030000250 UR - https://doi.org/10.17350/HJSE19030000250 Y2 - 2022 ER -
EndNote %0 Hittite Journal of Science and Engineering Diagnosing Diabetes with Machine Learning Techiques %A Ömer Faruk Akmeşe %T Diagnosing Diabetes with Machine Learning Techiques %D 2022 %J Hittite Journal of Science and Engineering %P -2148-4171 %V 9 %N 1 %R doi: 10.17350/HJSE19030000250 %U 10.17350/HJSE19030000250
ISNAD Akmeşe, Ömer Faruk . "Diagnosing Diabetes with Machine Learning Techiques". Hittite Journal of Science and Engineering 9 / 1 (March 2022): 9-18 . https://doi.org/10.17350/HJSE19030000250
AMA Akmeşe Ö. F. Diagnosing Diabetes with Machine Learning Techiques. Hittite J Sci Eng. 2022; 9(1): 9-18.
Vancouver Akmeşe Ö. F. Diagnosing Diabetes with Machine Learning Techiques. Hittite Journal of Science and Engineering. 2022; 9(1): 9-18.
IEEE Ö. F. Akmeşe , "Diagnosing Diabetes with Machine Learning Techiques", Hittite Journal of Science and Engineering, vol. 9, no. 1, pp. 9-18, Mar. 2022, doi:10.17350/HJSE19030000250