End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework.
End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework.
复制标题
基于AI的端到端护理诊断系统，用于分类呼吸系统疾病和早期发现Covid-19：一个理论框架。
DOI：
10.3389/fmed.2021.585578
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发表时间：
2021
影响因子：
3.9
通讯作者：
Chen C
中科院分区：
文献类型：
--
作者：
Belkacem AN;Ouhbi S;Lakas A;Benkhelifa E;Chen C
呼吸道症状可能由不同的潜在疾病引起，通常是由病毒感染引起的，如流感样疾病或冠状病毒等其他新出现的病毒。这些呼吸道病毒通常有共同的症状：咳嗽、高烧、鼻塞和呼吸困难。然而，早期诊断病毒类型可能至关重要，特别是在COVID-19大流行等病例中。导致COVID-19大流行传播的因素之一是诊断较晚或将COVID-19症状误解为常规流感样症状。研究表明，不同呼吸系统疾病的潜在原因之一可能是咳嗽声，咳嗽声有不同的类型和形式。因此，非常需要一种可靠的无实验室工具，用于早期和准确诊断，能够区分不同的呼吸道疾病，特别是在当前大流行期间。本概念论文讨论了端到端便携式系统的医学假设，该系统可以记录包括咳嗽（自愿或非自愿）在内的症状患者的数据，并将其转化为用于诊断的健康数据，并在机器学习的帮助下将其分类为不同的呼吸系统疾病，包括COVID-19。随着我们努力阻止COVID-19疾病在世界各地的传播，以及未来针对类似疾病的持续努力，我们提出的低成本和用户友好的理论解决方案可以在早期诊断中发挥重要作用。
Respiratory symptoms can be caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms: coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases, such as the COVID-19 pandemic. Among the factors that contributed to the spread of the COVID-19 pandemic were the late diagnosis or misinterpretation of COVID-19 symptoms as regular flu-like symptoms. Research has shown that one of the possible differentiators of the underlying causes of different respiratory diseases could be the cough sound, which comes in different types and forms. A reliable lab-free tool for early and accurate diagnosis, which can differentiate between different respiratory diseases is therefore very much needed, particularly during the current pandemic. This concept paper discusses a medical hypothesis of an end-to-end portable system that can record data from patients with symptoms, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly theoretical solution could play an important part in the early diagnosis.