Ágatha Yasmin de Sousa Araujo, Maylon Sivalcley da Costa Rocha, E. Alves, A. C. Campos
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引用次数: 0
摘要
在巴西,尤其是在亚马逊地区,老龄化是一个复杂而不规则的过程。这里发生的事情不能简单地用社会不平等来解释。这项研究的目的是介绍人工神经网络的发展以及巴西老年人健康老龄化分类的训练、验证和测试阶段。我们为老年人构建了快速诊断和健康筛查方案。该表单是在Microsoft Excel中离线开发的。宏(能够执行预编程任务的例程)是使用微软的Visual Basic for Applications (VBA)语言创建的。在混淆矩阵的分析中,训练(61.5%)、验证(60.0%)和测试(80.0%)三个阶段都获得了很好的准确率,这表明网络通过初始定义的输入和输出以及进行测试和验证的样本划分进行学习。在测试阶段,得到的ROC曲线真阳性率较好,假阳性率较低,接近Y轴(左侧),表明结果较好。我们对巴西东亚马逊地区的一个城市的36名社区活跃老人进行了一项试点研究。本研究分为数据采集、数据预处理、人工神经网络训练和评价方法四个部分。
An artificial neural network to classify healthy aging in elderly Brazilians
Aging in Brazil, especially in the Amazon, is a complex and irregular process. Something is happening here that cannot be explained simply due to social inequalities. The objective of this study was to present the development of an artificial neural network and the stages of training, validation and testing for the classification of healthy aging among elderly Brazilians. We constructed a protocol for rapid diagnosis and health screening for the elderly. The form was developed offline in Microsoft Excel. Macros (routines capable of performing pre-programmed tasks) were created using Microsoft's Visual Basic for Applications (VBA) language. In the analysis of the confusion matrix, good accuracy were obtained in all stages, training (61.5%), validation (60.0%) and test (80.0%), which indicates that the network learned through the inputs and outputs initially defined and during the sample divisions performed for testing and validation. In the test stage, a ROC curve was obtained with better true positive rates and lower false positive rates, being close to the Y axis (left side), thus indicating better results. We conducted a pilot study with thirty-six community active elderlies from a city in Eastern Amazonia, Brazil. This study was divided into four parts: data collection, data pre-processing, training of an artificial neural network and evaluation methods.