论文标题
使用人工神经网络对哮喘患者的智能风险警报
Intelligent Risk Alarm for Asthma Patients using Artificial Neural Networks
论文作者
论文摘要
哮喘是肺气道的慢性病。它导致呼吸道的炎症和狭窄,可防止空气流入气道,并导致呼吸频繁,喘不过气,伴有咳嗽和痰,在吸入引起过敏反应或呼吸系统刺激的物质后,伴有咳嗽和痰。医疗保健系统中的数据挖掘对于诊断和理解数据非常重要,因此由于诊断哮喘的复杂性,数据挖掘旨在解决诊断疾病的基本问题。预测大气中的化学物质非常重要,也是自上个世纪以来最困难的问题之一。在本文中,将提出和讨论化学物质对哮喘患者的影响。称为MQ5的传感器系统将用于检查大气中的烟雾和氮含量。 MQ5将插入手表中,该手表检查患者的烟雾和氮含量,如果这种气体影响哮喘患者,则系统应发出警告警报。它将基于使用包含一组化学物质(例如一氧化碳,NMHC(GT)酸气,C6H6(GT)汽油,NOX(GT)NOX(GT)氮氧化物和NO2(GT)NO2(GT)NITROGEN氮基因的数据,该算法(ANN)算法(ANN)算法。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,评估评分模型并达到了99.58%的分类精度。
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.