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Predictive modeling for chronic conditions.

机译:慢性病的预测模型。

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摘要

Chronic Diseases are the major cause of mortality around the world, accounting for 7 out of 10 deaths each year in the United States. Because of its adverse effect on the quality of life, it has become a major problem globally. Health care costs involved in managing these diseases are also very high. In this thesis, we will focus on two major chronic diseases Asthma and Diabetes, which are among the leading causes of mortality around the globe. It involves design and development of a predictive analytics based decision support system which uses five supervised machine learning algorithm to predict the occurrence of Asthma and Diabetes. This system helps in controlling the disease well in advance by selecting its best indicators and providing necessary feedback. Based on several risk factors such as blood pressure, BMI, age, ethnicity, smoking status etc., the system would be able to predict the vulnerability of a person to a particular disease which helps in taking necessary action to avoid the disease well in advance.
机译:慢性病是世界范围内主要的死亡原因,在美国每年占十分之七的死亡。由于其对生活质量的不利影响,它已成为全球的主要问题。控制这些疾病的医疗保健费用也很高。在本文中,我们将关注两种主要的慢性疾病:哮喘和糖尿病,它们是全球死亡的主要原因。它涉及基于预测分析的决策支持系统的设计和开发,该系统使用五种监督的机器学习算法来预测哮喘和糖尿病的发生。该系统通过选择最佳指标并提供必要的反馈,有助于提前很好地控制疾病。基于血压,BMI,年龄,种族,吸烟状况等多种风险因素,该系统将能够预测一个人对特定疾病的易感性,从而有助于提前采取必要措施避免该疾病。

著录项

  • 作者

    Jain, Ritesh.;

  • 作者单位

    Florida Atlantic University.;

  • 授予单位 Florida Atlantic University.;
  • 学科 Health care management.;Artificial intelligence.
  • 学位 M.S.
  • 年度 2015
  • 页码 90 p.
  • 总页数 90
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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