Diagnosis of Diabetes Using a Random Forest Algorithm

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Mosharrafzadeh Sadegh; Ravaei Bahman; Koozegar Ehsanollah

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Journal Paper

Paper Information

Journal: Iranian Journal of Diabetes and Metabolism Year:2021 | Volume:21 | Issue:2 Page(s): 92-100

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Information Journal Paper

Title

Diagnosis of Diabetes Using a Random Forest Algorithm

Author(s)

Mosharrafzadeh Sadegh | Ravaei Bahman | Koozegar Ehsanollah | Issue Writer Certificate

Keywords

DiseaseQ1

Data MiningQ1

DiabetesQ2

Random Forest AlgorithmQ1

Abstract

Background: Diabetes is the fourth leading cause of death in the world. And because so many people around the world have the Disease, or are at risk for it, Diabetes can be called the Disease of the century. Diabetes has devastating effects on the health of people in the community and if diagnosed late, it can cause irreparable damage to vision, kidneys, heart, arteries and so on. Therefore, it is necessary to have methods to diagnose this Disease in the early stages. In this article, Data Mining is used to diagnose Diabetes. Methods: The main algorithm used in this paper is the Random Forest Algorithm. To evaluate the efficiency of the proposed algorithm in diagnosing Diabetes, a data set was used that included 768 samples (patients) and had 8 characteristics. Because the stochastic forest algorithm is a hybrid algorithm created from several decision trees, it achieves high accuracy in diagnosing Diabetes. Results: Using this algorithm, we were able to increase the accuracy of Diabetes diagnosis to 99. 86%. Conclusion: Diabetes is the fourth leading cause of death in the world. Different algorithms have been used to diagnose this Disease. We tried to use an algorithm that has a very high degree of accuracy compared to other algorithms for diagnosing this Disease.

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References

Prediction and Diagnosis of Diabetes Mellitus using a Water Wave Optimization Algorithm

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APA: Copy

Mosharrafzadeh, Sadegh, Ravaei, Bahman, & Koozegar, Ehsanollah. (2021). Diagnosis of Diabetes Using a Random Forest Algorithm. JOURNAL OF DIABETES AND METABOLIC DISORDERS, 21(2 ), 92-100. SID. https://sid.ir/paper/415460/en

Vancouver: Copy

Mosharrafzadeh Sadegh, Ravaei Bahman, Koozegar Ehsanollah. Diagnosis of Diabetes Using a Random Forest Algorithm. JOURNAL OF DIABETES AND METABOLIC DISORDERS[Internet]. 2021;21(2 ):92-100. Available from: https://sid.ir/paper/415460/en

IEEE: Copy

Sadegh Mosharrafzadeh, Bahman Ravaei, and Ehsanollah Koozegar, “Diagnosis of Diabetes Using a Random Forest Algorithm,” JOURNAL OF DIABETES AND METABOLIC DISORDERS, vol. 21, no. 2 , pp. 92–100, 2021, [Online]. Available: https://sid.ir/paper/415460/en

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