梅利托斯糖尿病的系统诊断方法是基于网络的Naive Bayes方法(案例研究:Puskesmas地区Sambit Ponorogo)

Rudi Aristanto, A. Chandra
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引用次数: 0

摘要

糖尿病是一种以高血糖(葡萄糖)水平为特征的疾病。糖尿病被称为无声杀手,因为患者没有意识到它,当并发症已经发生时才被发现。病人在Sambit区保健中心经历的并发症是基于访谈的结果。Sambit地区保健中心20%的病人患有并发症。这一不断增加的数字是由于诊断延误和不健康的生活方式以及缺乏信息,因此许多患者是在并发症发生后才被诊断出来的。早期诊断将减少并发症的风险。因此,无论患者是否患有糖尿病,都需要专家系统作为诊断工具。基于这个问题,我们选择了朴素贝叶斯算法,因为它是基于比较旧数据和新数据的分类,从这个问题中,编译器通过观察过去的事件,将患有糖尿病的人与那些没有达到症状水平的人进行分类。从对20例患者数据进行的测试结果来看,该系统的准确率为100%(基于事实和症状)。从这项研究可以得出结论,糖尿病是一种危险的疾病,仍然需要早期预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sistem Pakar Diagnosis Penyakit Diabetes Mellitus Dengan Menggunkan Metode Naive Bayes Berbasis Web (Studi Kasus : Puskesmas Kecamatan Sambit Ponorogo)
Diabetes mellitus is a disease characterized by high blood sugar (glucose) levels. DM is known as the silent killer because the sufferer is not aware of it and is identified when complications has already occured.Complications experienced by patients at the Sambit District Health Center were based on the results of interviews. 20% of patients at the Sambit District Health Center suffered from complications. This increasing number is due to delays in diagnosis and unhealthy lifestyles as well as a lack of information so that many patients are diagnosed after complications occured. Early diagnosis will reduce the risk of complications. From this point, an expert system is needed as a diagnostic tool whether the patient suffers from diabetes mellitus or not. Based on this problem, the Naive Bayes algorithm is chosen because it is based on classification by comparing old data and new data, and from this problem the compiler classifies a person who suffers from Diabetes Mellitus with those who are not at the level of symptoms suffered by looking at the events that have passed. From the results of tests that have been carried out from 20 patient data, the percentage of accuracy of the system is 100% (based on facts and symptoms). From this study, it can be concluded that diabetes mellitus is a dangerous disease and still requires early prevention.
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