基于云的医疗物联网电子健康服务——基于深度卷积神经网络的脑肿瘤检测模型

Q2 Social Sciences
M. Ganesan, N. Sivakumar, M. Thirumaran
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引用次数: 0

摘要

目前,电子医疗服务为医疗保健部门提供了各种决策支持系统。这些系统利用医疗物联网(IoMT)设备和云平台为数百万人提供服务。在本文中,我们利用卷积神经网络(CNN)开发了一个基于云的物联网脑肿瘤检测模型。在这里,使用医疗设备捕获输入的MRI大脑图像,并使用物联网设备将数据传输到云端。在云中,可以执行D-CNN模型来识别疾病的存在,并将脑肿瘤分类为恶性或良性。将所提出的D-CNN模型应用于一组基准BRATS 2015挑战数据集。该模型灵敏度为97.17,特异度为98.77,准确率为98.07,分类器性能最佳。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Internet of Medical Things with Cloud based e-Health Services for Brain Tumor Detection Model using Deep Convolution Neural Network
In the present days, e-health services offer various decision support systems in healthcare sector. These systems make use of internet of medical things (IoMT) devices and cloud platform to offer services to millions of people. In this paper, we develop an IoT with cloud-based brain tumour detection model using convolution neural network (CNN). Here, the input MRI brain images are captured by the use of medical equipments as well as IoT devices is used to transmit data to the cloud. In the cloud, the D-CNN model can be executed to identify the presence of disease and classify the brain tumour as malignant or benign. The presented D-CNN model is employed to a set of benchmark BRATS 2015 challenge dataset. The presented model attains maximum classifier performance with the sensitivity value of 97.17, specificity of 98.77 and accuracy of 98.07.
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来源期刊
Electronic Government
Electronic Government Social Sciences-Public Administration
CiteScore
2.30
自引率
0.00%
发文量
48
期刊介绍: Electronic Government, a fully refereed journal, publishes articles that present current practice and research in the area of e-government.
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