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A mobile platform for automated screening of asthma and chronic obstructive pulmonary disease

机译:自动筛查哮喘和慢性阻塞性肺疾病的移动平台

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Chronic Obstructive Pulmonary Disease (COPD) and asthma each represent a large proportion of the global disease burden; COPD is the third leading cause of death worldwide and asthma is one of the most prevalent chronic diseases, afflicting over 300 million people. Much of this burden is concentrated in the developing world, where patients lack access to physicians trained in the diagnosis of pulmonary disease. As a result, these patients experience high rates of underdiagnosis and misdiagnosis. To address this need, we present a mobile platform capable of screening for Asthma and COPD. Our solution is based on a mobile smart phone and consists of an electronic stethoscope, a peak flow meter application, and a patient questionnaire. This data is combined with a machine learning algorithm to identify patients with asthma and COPD. To test and validate the design, we collected data from 119 healthy and sick participants using our custom mobile application and ran the analysis on a PC computer. For comparison, all subjects were examined by an experienced pulmonologist using a full pulmonary testing laboratory. Employing a two-stage logistic regression model, our algorithms were first able to identify patients with either asthma or COPD from the general population, yielding an ROC curve with an AUC of 0.95. Then, after identifying these patients, our algorithm was able to distinguish between patients with asthma and patients with COPD, yielding an ROC curve with AUC of 0.97. This work represents an important milestone towards creating a self-contained mobile phone-based platform that can be used for screening and diagnosis of pulmonary disease in many parts of the world.
机译:慢性阻塞性肺疾病(COPD)和哮喘分别占全球疾病负担的很大一部分; COPD是全球第三大死亡原因,哮喘是最流行的慢性疾病之一,折磨着3亿多人。这种负担的大部分集中在发展中国家,那里的患者缺乏与受过肺部疾病诊断培训的医生的联系。结果,这些患者的误诊和误诊率很高。为了满足这一需求,我们提出了一种能够筛查哮喘和COPD的移动平台。我们的解决方案基于智能手机,包括电子听诊器,峰值流量计应用程序和患者问卷。该数据与机器学习算法相结合,以识别患有哮喘和COPD的患者。为了测试和验证设计,我们使用自定义移动应用程序从119名健康和患病的参与者中收集了数据,并在PC计算机上运行了分析。为了进行比较,所有受试者均由经验丰富的肺科医生使用完整的肺部测试实验室进行检查。使用两阶段逻辑回归模型,我们的算法首先能够从一般人群中识别出哮喘或COPD患者,其ROC曲线的AUC为0.95。然后,在识别出这些患者之后,我们的算法能够区分哮喘患者和COPD患者,得出ROC曲线,AUC为0.97。这项工作代表了一个重要的里程碑,即创建了一个可用于全球许多地区的筛查和诊断肺部疾病的基于手机的独立平台。

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