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首页> 外文期刊>Journal of medical systems >Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches
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Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches

机译:使用分类方法的远程医疗支持的慢性伤口组织预测

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摘要

Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due to unavailability of expert doctors. This problem generally affects older ageing people. So there is a need of better assessment facility to the remote people in tele-medicine framework. Here we have proposed a CW tissue prediction and diagnosis under telemedicine framework to classify the tissue types using linear discriminant analysis (LDA). The proposed telemedicine based wound tissue prediction (TWTP) model is able to identify wound tissue and correctly predict the wound status with a good degree of accuracy. The overall performance of the proposed wound tissue prediction methodology has been measured based on ground truth images. The proposed methodology will assist the clinicians to take better decision towards diagnosis of CW in terms of quantitative information of three types of tissue composition at low-resource set-up.
机译:远程医疗通过通信系统和健康信息学的发展帮助以电子方式向患者提供健康服务。由于无法获得专家医生的帮助,在远距离进行慢性伤口(CW)检测及其愈合率评估非常困难。此问题通常会影响老年人。因此,需要在远程医疗框架中为远程人员提供更好的评​​估工具。在这里,我们提出了在远程医疗框架下的连续波组织预测和诊断,以使用线性判别分析(LDA)对组织类型进行分类。所提出的基于远程医疗的伤口组织预测(TWTP)模型能够识别伤口组织并以良好的准确度正确预测伤口状态。所提出的伤口组织预测方法的总体性能已根据地面真实图像进行了测量。所提出的方法将帮助临床医生根据低资源设置下三种组织组成类型的定量信息,对CW的诊断做出更好的决策。

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