ANALISIS DETERMINAN DAN PREDIKSI PENYAKIT DIABETES MELITUS TIPE 2 MENGGUNAKAN METODE MACHINE LEARNING: SCOPING REVIEW

Rapael Ginting, Ermi Girsang, J. Ginting, H. Hartono
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Abstract

ABSTRACT The prevalence of diabetes mellitus is increasing globally, nationally, and regionally, and most of them are type 2 diabetes mellitus, which can cause complications, economic losses, and death. The purpose of this study is to examine the analysis of determinants and predictions of type 2 diabetes mellitus using machine learning methods. This study uses the scoping review method to view, accumulate and synthesize the results of previous studies on the analysis of determinants and predictions of type 2 diabetes mellitus using machine learning methods. The inclusion criteria in this study were articles published in the indexed journal database PubMed, Google Scholar, Crossref in English and Indonesian, journals published in the 2017-2021 range and 15 articles that met the inclusion criteria. The search results were a total of 860 articles from 3 databases (PubMed, Google Scholar, Crossref) in which 98 of them were duplicate articles and were excluded. Of the remaining 762 articles, 142 were not full text and 605 were excluded after eligibility screening because they were irrelevant. The remaining 15 articles were systematically reviewed and qualitatively analyzed using the NVIVO-12 Plus application. From the analysis of previous studies concluded that age, obesity, family history of disease, and lack of physical activity are risk factors for type 2 diabetes mellitus, while the gender variable from the analysis of previous research shows that there is no significant relationship between gender and type 2 diabetes. With early prediction of type 2 diabetes mellitus preventive measures, treatment can be carried out immediately and reduce the incidence of complications that can worsen the condition of people with type 2 diabetes.    
使用机器学习方法:进行检修
摘要糖尿病的发病率在全球、国家和地区均呈上升趋势,其中以2型糖尿病居多,可造成并发症、经济损失和死亡。本研究的目的是研究使用机器学习方法分析2型糖尿病的决定因素和预测。本研究采用scoping review方法,对以往使用机器学习方法分析2型糖尿病的决定因素和预测的研究结果进行查看、积累和综合。本研究的纳入标准是发表在索引期刊数据库PubMed、谷歌Scholar、Crossref的英文和印文文章、2017-2021年范围内发表的期刊以及符合纳入标准的15篇文章。检索结果来自PubMed、b谷歌Scholar、Crossref 3个数据库共860篇文章,其中98篇为重复文章,被排除。在剩余的762篇文章中,142篇不是全文,605篇在资格筛选后被排除,因为它们不相关。使用NVIVO-12 Plus应用程序对其余15篇文章进行系统回顾和定性分析。从以往研究分析得出,年龄、肥胖、家族史、缺乏体育锻炼是2型糖尿病的危险因素,而从以往研究分析的性别变量来看,性别与2型糖尿病的关系不显著。通过对2型糖尿病预防措施的早期预测,可以立即进行治疗,减少并发症的发生,使2型糖尿病患者的病情恶化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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