Machine Learning Algorithms for Diabetes Prediction: A Review Paper

Abir Al-Sideiri, Z. C. Cob, S. M. Drus
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引用次数: 6

Abstract

The early diagnosis of the diabetes disease is a very important for cure process, and that provides an ease process of treatment for both the patient and the doctor. At this point, statistical methods and data mining algorithms can provide significance chances for early diagnosis of diabetes mellitus (DM). In the literature, many studies have been published for solution of this problem. Initially, these studies are analyzed in detail and classified according to their methodologies. The main aim of this paper is to provide the comprehensive and detailed review of the diagnosis of diabetes by machine learning algorithms. Also, this paper presents a literature review on the diagnosis diabetes up to the mid of 2019. This paper provides to guide future research and knowledge accumulation and creation of classification and prediction techniques in diagnosis of diabetes. This study shows that the Support Vector Machine (SVM) algorithm is the most used machine learning algorithms and it provide more accurate and powerful results.
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糖尿病预测的机器学习算法:综述论文
糖尿病的早期诊断对糖尿病的治愈过程非常重要,这为患者和医生提供了一个轻松的治疗过程。此时,统计方法和数据挖掘算法可以为糖尿病(DM)的早期诊断提供有意义的机会。在文献中,已经发表了许多研究来解决这个问题。首先,对这些研究进行了详细的分析,并根据其方法进行了分类。本文的主要目的是通过机器学习算法对糖尿病的诊断提供全面和详细的综述。此外,本文还对截至2019年中期的糖尿病诊断文献进行了综述。为今后的研究和糖尿病诊断分类预测技术的知识积累和创新提供指导。研究表明,支持向量机(SVM)算法是最常用的机器学习算法,它提供了更准确和强大的结果。
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