使用机器学习方法从医学图像和/或患者症状中检测COVID-19的综述论文

Akshay Kumar Siddhu, Ashok Kumar, Shakti Kundu
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引用次数: 8

摘要

新型冠状病毒COVID-19在中国武汉首次被发现。COVID-19确诊患者的特征是发烧、疲劳和干咳。新型冠状病毒(COVID-19)疫情正在全球蔓延。在这篇综述文章中,我们使用了普通细菌性肺炎、确诊Covid-19感染和普通病例的x射线、ct扫描图像数据库来自动检测冠状病毒感染。本研究的目的是评估COVID-19获取的有效性。在COVID-19情景下,全球感染病例数量大幅增加。由于这一事实,医疗专家和受感染患者作出了一项重要决定,即在合理的时间内采用各种医疗设施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review Paper for Detection of COVID-19 from Medical Images and/ or Symptoms of Patient using Machine Learning Approaches
The new type of coronavirus COVID-19 virus was first detected in Wuhan-China. A COVID-19 certified patient is characterized by fever, fatigue, and dry cough. The coronavirus (COVID-19) epidemic is spreading worldwide. In this review paper, a database of X-ray, CT-Scan images from patients with common bacterial pneumonia, confirmed Covid-19 infection, and common cases, were used to automatically detect Coronavirus infection. The purpose of the study was to evaluate the effectiveness of COVID-19 acquisition. During the COVID-19 scenario, the number of infected cases rises in huge number globally. Due to this fact, a vital decision had been taken by medical experts and infected patients to adopt various medical facilities within a reasonable amount of time.
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