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A PREDICTIVE MODEL FOR KIDNEY FAILURE E-HEALTH

机译:肾衰竭电子健康的预测模型

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摘要

Big data is the large set of dataset. It involves extraction, selection, analyzing and interpolation of data. Big data is used wide assortment in medical fields for analyzing the patient's medical history, prediction of future effects and clinical decision making. It can also be used as a tool to store large number of data. It helps us to understand the diseases and also paves way to predict the disease and its future effects caused by the disease. In this paper we use RBFNN (Radial Basis Function Neural Network) with classifier algorithm with the use of parameters to determine the condition of a patient as a normal or a kidney failure patient. The proposed method reveals the stages of the kidney failure patient and treatment and clinical decision.
机译:大数据是大量数据集。它涉及提取,选择,分析和数据的插值。大数据用于医疗领域的广泛分类,用于分析患者的病史,预测未来效应和临床决策。它也可以用作存储大量数据的工具。它有助于我们了解疾病,也铺平了预测疾病的方式及其未来的疾病。在本文中,我们使用RBFNN(径向基函数神经网络)与分类器算法使用参数来确定患者作为正常或肾功能衰竭患者的病症。该方法揭示了肾衰竭患者和治疗和临床决策的阶段。

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