Quantitative Analysis of COVID-19 Patients: A Preliminary Statistical Result of Deep Learning Artificial Intelligence Framework

Quantitative Analysis of COVID-19 Patients: A Preliminary Statistical Result of Deep Learning Artificial Intelligence Framework

Soobia Saeed, N. Z. Jhanjhi, Memood Naqvi, Mamoona Humayun, Vasaki Ponnusamy
Copyright: © 2021 |Pages: 25
DOI: 10.4018/978-1-7998-7114-9.ch011
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Abstract

A new coronavirus-CoV-2 virus has caused disease outbreaks in many countries, and the number of cases is increasing rapidly through transmission from person to person. Clinical acoustics for SARS-CoV-2 patients are crucial to distinguish them from other respiratory infections. Symptomatic sufferers can also have pulmonary lesions on the photographs. A computerized tomography study in patients with suspected COVID-19 pneumonia consists of using a high-resolution approach (HRCT). Artificial intelligence applications need to be useful in categorizing the illness to an awesome severity and integrating the structured file, organized consistent with subjective issues, with objective and quantitative checks of the amount of the lesions. Data indicate the statistical document of the world in trendy. This method, with the aid of a coloring map, identifies floor glass in submission processing and separates it from consolidation and units it as a percentage in respect to the balanced weight loss program.
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Introduction

The World Health Organisation (WHO) caused a new Worldwide Coronavirus outbreak (Covid-19) on 11 March 2020. The Director-General of the World Health Organization, Tedros Adhanom Ghebreyesus, said that the explosive rate of cases has increased thirteen times in recent weeks (Cucinotta & Vanelli, 2020).The outbreak of the extreme acute respiration syndrome (SARS-CoV-2) virus has already taken on epidemiological dimensions, affecting greater than one hundred nations in a few weeks. In order to prepare health structures around the arena, a worldwide reaction is wanted.

In December 2019, coronavirus disease (COVID-19) caused by Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) appeared in Wuhan, the capital of Hubei Province of China (Pan, Ye, Sun, Gui, Liang, Li et al, 2020).The virus has been spreading hastily throughout China and lots of different countries/areas, with a hundred and thirty-five, 336 showed cases global and 79,235 deaths recorded by using the WHO as of 8 April 2020(Cucinotta & Vanelli, 2020). Most COVID-19 patients have mild symptoms but others can even experience severe pneumonia, pulmonary oedema, acute respiratory distress syndrome (ARDS), a few syndromes of organ failure, or even death. In the COVID-19 epidemiological study conducted by the Chinese Center for Disease Control (CDC), out of the 44 cases reported, patients with mild diseases accounted for 13.8 percent and patients with extreme disease for 44,672 cases confirmed, those with serious disease as 13.8 per cent of diseases and 4.7 per cent of patients with hyperpathology(Pan, Ye, Sun, Gui, Liang, Li et al, 2020). The standard mortality rate changed into 49. 0 percentage for chronically unwell sufferers and these sufferers the average threat of demise during a 10-day follow-up changed into 0.325(Pan, Ye, Sun, Gui, Liang, Li et al, 2020).

Other current research confirmed that the 28-day death rate changed to 61.50% among those with chronic diseases (Novel CPERE, 2020). cIt is crucial to consider the danger factors associated with severe illness and to recognize patients that are most vulnerable to adverse effects at an early stage, enabling you to concentrate on prevention and corrective efforts(WHO, 2020).Several biomarkers have been used to assess the severity of infectious pneumonia patients and to guide medical approaches, along with the Diploma of Acute Body Formation and Continuous Fitness Assessment 2 (APACHE-II), as well as laboratory measurements that overlap neutrophil index (NLR) and lactate score (6- 8]. Such medical biomarkers were used for analysis of patients suffering from acute respiratory distress syndrome (Huang et al., 2006; Jiang et al., 2019; Wu et al., 2018) or extreme acute respiratory syndrome (SARS)(Nishiyama et al., 2020). However, they're no longer specific sufficient to determine contamination and every so often require intrusive testing, which may boost the hazard of hospital treatment-associated publicity to the virus and contamination. In addition, factor scoring structures which include APACHE-II is self-eating and time-ingesting that can postpone clinical remedy in opposition to outbreaks of COVID-19. Recently a high stage of dimer-d in patients with COVID-19 has been stated as a hazard aspect for terrible outcomes (Tai et al., 2004; Zhou et al., 2020).

Figure 1.

Tracking vicinity of quantity of showed instances and deaths from the coronavirus disorder (COVID-19) in locations with Humanitarian Response Plans (HRPs).

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This visual indicates the range of confirmed Coronavirus Disease (COVID-19) cases and deaths in places where Humanitarian Response Plans (HRP) exists. The evidence surrounding COVID-19 came from the World Health Organization (WHO). .International locations include Afghanistan, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Colombia, the Democratic Republic of the Congo, Ethiopia, Haiti, Iraq, Libya, Mali, Myanmar, Nigeria, the Occupied Palestinian Territories and Somalia. South Somalia, Somalia, Iraq, Russia, Libya, Zimbabwe and Yemen. You can carry more countries, as needed.

Figure 2.

The CSSE software at Johns Hopkins University tracks the progression of SARS-CoV-2 in almost real time using a map-centric interface (using ArcGIS Online) that extracts relevant data from the CDC (Centers for Disease Control and Prevention). For diseases) from WHO and the USA, ECDC (European Centre for Disease Prevention and Control), Chinese Centre for Control and Prevention of Diseases (CCDC), NHC (China's Public Health Commission) and Dingxiangyuan (DXY, China); Day of recording of the screens: 16 February 2020.

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