基于人工神经网络的哮喘患者智能风险预警
Intelligent Risk Alarm for Asthma Patients using Artificial Neural Networks
摘要：
哮喘是一种慢性肺部气道疾病。它导致炎症和呼吸道变窄，从而阻止空气流入呼吸道，并在吸入引起过敏反应或刺激呼吸系统的物质后导致呼吸急促伴喘息伴随咳嗽和痰的频繁发作。数据挖掘在医疗系统中对于诊断和理解数据非常重要，由于哮喘诊断的复杂性，数据挖掘旨在解决疾病诊断中的基本问题。预测大气中的化学物质非常重要，也是上个世纪以来最困难的问题之一。本文将介绍和讨论化学品对哮喘患者的影响。名为MQ5的传感器系统将用于检测大气中的烟雾和氮含量。MQ5将被插入手表中，用于检查患者场所的烟雾和氮气含量，如果这种气体影响哮喘患者，系统将发出警告警报。它将基于人工神经网络（ANN）算法，该算法使用包含一系列化学品的数据构建，如一氧化碳，NMHC（GT）酸性气体，C6H6（GT）汽油，NOx（GT）氮氧化物和NO2（GT）二氧化氮。温度和湿度也将被使用，因为它们会对哮喘患者产生负面影响。最后，评级模型进行了评估，并取得了99.58%的分类准确率。
英文摘要：
Asthma is a chronic disease of the airways of the lungs. It results in inflammation and narrowing of the respiratory passages, which prevents air flow into the airways and leads to frequent bouts of shortness of breath with wheezing accompanied by coughing and phlegm after exposure to inhalation of substances that provoke allergic reactions or irritation of the respiratory system. Data mining in healthcare system is very important in diagnosing and understanding data, so data mining aims to solve basic problems in diagnosing diseases due to the complexity of diagnosing asthma. Predicting chemicals in the atmosphere is very important and one of the most difficult problems since the last century. In this paper, the impact of chemicals on asthma patient will be presented and discussed. Sensor system called MQ5 will be used to examine the smoke and nitrogen content in the atmosphere. MQ5 will be inserted in a wristwatch that checks the smoke and nitrogen content in the patients place, the system shall issue a warning alarm if this gas affects the person with asthma. It will be based on the Artificial Neural Networks (ANN) algorithm that has been built using data that containing a set of chemicals such as carbon monoxide, NMHC (GT) acid gas, C6H6 (GT) Gasoline, NOx (GT) Nitrogen Oxide, and NO2 (GT) Nitrogen Dioxide. The temperature and humidity will be also used as they can negatively affect asthma patient. Finally, the rating model was evaluated and achieved 99.58% classification accuracy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
