使用数据挖掘的智能医疗保健系统

Subasish Mohapatra, P. Patra, Subhadarshini Mohanty, Bhagyashree Pati
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引用次数: 13

摘要

医疗保健行业收集了大量的医疗保健数据,不幸的是,这些数据没有被“挖掘”,以发现隐藏的信息,从而进行有效的决策。数据挖掘已成为获得诊断结果的当前趋势。医疗保健行业收集了大量未挖掘的数据,以发现隐藏的信息,从而进行有效的诊断和决策。数据挖掘是从海量数据集中提取隐藏信息,对数据中有效且唯一的模式进行分类的过程。世界各国的研究人员都在研究多智能体或本体来开发卫生保健领域的系统。这可能已经发生了很多次,你或别人需要医生的帮助,但由于某种原因,他们不在。健康管理系统是一个终端用户支持和在线咨询项目。在这里,我们提出了一个系统,允许用户通过智能医疗在线系统获得健康问题的指导。本文的目的是使用聚类技术,K-means算法来预测慢性肾脏疾病(CKD),心脏病和肝脏疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Health Care System using Data Mining
The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not "mined" to discover hidden information for effective decision making. Data mining has been a current trend for attaining diagnostic results. Huge amount of unmined data is collected by the healthcare industry in order to discover hidden information for effective diagnosis and decision making. Data mining is the process of extracting hidden information from massive dataset, categorizing valid and unique patterns in data. Researchers all over the world are working in either multi agents or in ontologies for developing system in health care domain. It might have happened so many times that you or someone need doctor help but they are not available due to some reason. The health management system is an end user support and online consultation project. Here we propose a system that allows users to get guidance on their health issues through an intelligent health care online system. The objective of our paper is to predict Chronic Kidney Disease (CKD), Heart Disease and Liver Disease using clustering technique, K-means algorithm.
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