基于Apriori算法的人类抑郁预测模型

L. Jena, N. K. Kamila
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引用次数: 14

摘要

抑郁症作为现代最新的一种流行病,其发病水平、成因及防治一直受到研究者的关注。根据精神科医生的说法,这不是一种心理障碍,但它会产生协调失败的刺激和模拟。最严重的抑郁水平可能是一个人试图自杀,失去精力,失眠等。这种流行病对个人和公共卫生造成严重挑战。每年有成千上万的人患有抑郁症,只有少数人得到适当的治疗。鉴于预测的趋势,本文提出并试图找出受抑郁症影响的人群及其疾病程度。这项工作是自我激励的。本文采用先验算法和关联规则挖掘的概念,从大量的相关人员数据库中提取信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Model for Prediction of Human Depression Using Apriori Algorithm
Depression a latest epidemic of modern era has always drawn the attention of researcher's to find & evaluate the level, causes & prevention. According to psychiatrists it's not a psychological disorder but it creates the stimulation & simulation of co-ordination failure. The worst case of the leading depression level may contemplates a person to attempt suicide, loss of energy, insomnia etc. This epidemic causes severe personal and public health challenges. Each year thousands of millions of people are suffering from depression and a few receives adequate treatment. Keeping view at the trend of predicting, this paper has been proposed & tried to find out the persons affected by depression and their level of illness. The work is self motivated. Here the concept of apriori algorithm & association rule mining is used in order to extract the information from a large collection of database of concerned persons.
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