scholarly journals Deep Learning Applications and Perspectives COVID 19

2020 ◽  
pp. 487-490
Author(s):  
Suresh P ◽  
Robert P ◽  
Padmavathi A
Keyword(s):  
Deep Learning ◽  
Learning Algorithm ◽  
Control Measures ◽  
World Health ◽  
Technological Support ◽  
Deep Learning Algorithm ◽  
Corona Virus ◽  
The World ◽  
The Government ◽  
Health Organization

An anticipated outbreak of corona virus (COVID-19) brings out the severe acute respiratory syndrome and corona-virus-2(SARS-COV-2) attacked in Wuhan city, china beginning of February 2020. World health organization (WHO) announced the outburst of pandemic disease through public health emergency of international concern. A variety of control measures has been taken by the government to control the disease. The investigation can be done about the pathogen and current epidemic. The world healthcare system has a major concern for new infectious diseases like covid-19 and needs new technological support. Deep learning in Artificial intelligence (AI) helps the world by safeguard the people from pandemic disease. Our aim is to investigate the AI based deep learning algorithm to analyze, prevent and prepare to defend against covid-19 and similar infectious disease.

scholarly journals COVID-19 outbreak, social distancing and mass testing in Kenya - Insights from a mathematical model 

2020 ◽  
Author(s):  
Rachel Waema Mbogo ◽  
John W. Odhiambo
Keyword(s):  
Informal Settlement ◽  
Target Population ◽  
Control Measures ◽  
World Health ◽  
Transmission Model ◽  
Global Public Health ◽  
The World ◽  
The Government ◽  
Novel Coronavirus ◽  
Health Organization

Abstract As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus ( COVID -19), which started as an outbreak of pneumonia of unknown cause in the Wuhan city of China in December 2019. Within days and weeks, the COVID -19 pandemic had spread to over 210 countries. By the end of April, COVID -19 had caused over three million confirmed cases of infections and 230,000 fatalities globally. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.We employed a SEIHCRD delay differential mathematical transmission model with reported Kenyan data on cases of COVID -19 to estimate how transmission varies over time and which population to target for mass testing. The model is concise in structure, and successfully captures the course of the COVID -19 outbreak, and thus sheds light on understanding the trends of the outbreak and the vulnerable populations. The results from the model gives insights to the government on the population to target for mass testing. The government should target population in the informal settlement for mass testing. People with pre-existing medical and non-medical conditions should be identified and given special medical care. With aggressive effective mass testing and adhering to the government directives and guidelines, we can get rid of COVID -19 epidemic.

scholarly journals Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection

2021 ◽  
Vol 15 (9) ◽  
pp. e0009677
Author(s):  
Elena Dacal ◽  
David Bermejo-Peláez ◽  
Lin Lin ◽  
Elisa Álamo ◽  
Daniel Cuadrado ◽  
...  
Keyword(s):  
Deep Learning ◽  
Learning Algorithm ◽  
Neglected Tropical Diseases ◽  
Mobile App ◽  
World Health ◽  
Automatic Assessment ◽  
Deep Learning Algorithm ◽  
Short Period ◽  
Health Organization ◽  
Remote Analysis

Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is the diagnosis method recommended by the World Health Organization (WHO) although it often presents a decreased sensitivity in low transmission settings and it is labour intensive. Visual reading of Kato-Katz preparations requires the samples to be analyzed in a short period of time since its preparation. Digitizing the samples could provide a solution which allows to store the samples in a digital database and perform remote analysis. Artificial intelligence (AI) methods based on digitized samples can support diagnosis by performing an objective and automatic quantification of disease infection. In this work, we propose an end-to-end pipeline for microscopy image digitization and automatic analysis of digitized images of STH. Our solution includes (a) a digitization system based on a mobile app that digitizes microscope samples using a 3D printed microscope adapter, (b) a telemedicine platform for remote analysis and labelling, and (c) novel deep learning algorithms for automatic assessment and quantification of parasitological infections by STH. The deep learning algorithm has been trained and tested on 51 slides of stool samples containing 949 Trichuris spp. eggs from 6 different subjects. The algorithm evaluation was performed using a cross-validation strategy, obtaining a mean precision of 98.44% and a mean recall of 80.94%. The results also proved the potential of generalization capability of the method at identifying different types of helminth eggs. Additionally, the AI-assisted quantification of STH based on digitized samples has been compared to the one performed using conventional microscopy, showing a good agreement between measurements. In conclusion, this work has presented a comprehensive pipeline using smartphone-assisted microscopy. It is integrated with a telemedicine platform for automatic image analysis and quantification of STH infection using AI models.

scholarly journals COVID-19 outbreak, social distancing and mass testing in Kenya - Insights from a mathematical model 

2020 ◽  
Author(s):  
Rachel Waema Mbogo ◽  
John W. Oddhiambo
Keyword(s):  
Informal Settlement ◽  
Target Population ◽  
Control Measures ◽  
World Health ◽  
Transmission Model ◽  
Global Public Health ◽  
The World ◽  
The Government ◽  
Novel Coronavirus ◽  
Health Organization

Abstract As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus ( COVID -19), which started as an outbreak of pneumonia of unknown cause in the Wuhan city of China in December 2019. Within days and weeks, the COVID -19 pandemic had spread to over 210 countries. By the end of April, COVID -19 had caused over three million confirmed cases of infections and 230,000 fatalities globally. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.We employed a SEIHCRD delay differential mathematical transmission model with reported Kenyan data on cases of COVID -19 to estimate how transmission varies over time and which population to target for mass testing. The model is concise in structure, and successfully captures the course of the COVID -19 outbreak, and thus sheds light on understanding the trends of the outbreak and the vulnerable populations. The results from the model gives insights to the government on the population to target for mass testing. The government should target population in the informal settlement for mass testing. People with pre-existing medical and non-medical conditions should be identified and given special medical care. With aggressive effective mass testing and adhering to the government directives and guidelines, we can get rid of COVID -19 epidemic.

ARIMA model for forecasting COVID-19 Death cases in India (Preprint)

2020 ◽  
Author(s):  
Jeya Sutha M
Keyword(s):  
Arima Model ◽  
Public Health Emergency ◽  
World Health ◽  
The People ◽  
The World ◽  
The Status ◽  
The Government ◽  
Health Organization ◽  
Spread Of Infection ◽  
Death Cases

UNSTRUCTURED COVID-19, the disease caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a highly contagious disease. On January 30, 2020 the World Health Organization declared the outbreak as a Public Health Emergency of International Concern. As of July 25, 2020; 15,947,292 laboratory-confirmed and 642,814 deaths have been reported globally. India has reported 1,338,928 confirmed cases and 31,412 deaths till date. This paper presents different aspects of COVID-19, visualization of the spread of infection and presents the ARIMA model for forecasting the status of COVID-19 death cases in the next 50 days in order to take necessary precaution by the Government to save the people.

Characterizing the effectiveness of COVID-19 mitigation measures: A data-centric approach (Preprint)

2020 ◽  
Author(s):  
Lukman Olagoke ◽  
Ahmet E. Topcu
Keyword(s):  
Control Measure ◽  
Control Measures ◽  
World Health ◽  
Mitigation Measures ◽  
Effective Control ◽  
The World ◽  
Decision Making Processes ◽  
And Performance ◽  
Health Organization ◽  
The Impact

BACKGROUND COVID-19 represents a serious threat to both national health and economic systems. To curb this pandemic, the World Health Organization (WHO) issued a series of COVID-19 public safety guidelines. Different countries around the world initiated different measures in line with the WHO guidelines to mitigate and investigate the spread of COVID-19 in their territories. OBJECTIVE The aim of this paper is to quantitatively evaluate the effectiveness of these control measures using a data-centric approach. METHODS We begin with a simple text analysis of coronavirus-related articles and show that reports on similar outbreaks in the past strongly proposed similar control measures. This reaffirms the fact that these control measures are in order. Subsequently, we propose a simple performance statistic that quantifies general performance and performance under the different measures that were initiated. A density based clustering of based on performance statistic was carried out to group countries based on performance. RESULTS The performance statistic helps evaluate quantitatively the impact of COVID-19 control measures. Countries tend show variability in performance under different control measures. The performance statistic has negative correlation with cases of death which is a useful characteristics for COVID-19 control measure performance analysis. A web-based time-line visualization that enables comparison of performances and cases across continents and subregions is presented. CONCLUSIONS The performance metric is relevant for the analysis of the impact of COVID-19 control measures. This can help caregivers and policymakers identify effective control measures and reduce cases of death due to COVID-19. The interactive web visualizer provides easily digested and quick feedback to augment decision-making processes in the COVID-19 response measures evaluation. CLINICALTRIAL Not Applicable

scholarly journals Coronavirus Disease 2019 (COVID-19): Emerging and Future Challenges for Dental and Oral Medicine

2020 ◽  
Vol 99 (5) ◽  
pp. 481-487 ◽  
Author(s):  
L. Meng ◽  
F. Hua ◽  
Z. Bian
Keyword(s):  
Public Health ◽  
Infection Control ◽  
Control Measures ◽  
World Health ◽  
Infection Control Measures ◽  
Dental Practitioners ◽  
The World ◽  
Essential Knowledge ◽  
Novel Coronavirus ◽  
Health Organization

The epidemic of coronavirus disease 2019 (COVID-19), originating in Wuhan, China, has become a major public health challenge for not only China but also countries around the world. The World Health Organization announced that the outbreaks of the novel coronavirus have constituted a public health emergency of international concern. As of February 26, 2020, COVID-19 has been recognized in 34 countries, with a total of 80,239 laboratory-confirmed cases and 2,700 deaths. Infection control measures are necessary to prevent the virus from further spreading and to help control the epidemic situation. Due to the characteristics of dental settings, the risk of cross infection can be high between patients and dental practitioners. For dental practices and hospitals in areas that are (potentially) affected with COVID-19, strict and effective infection control protocols are urgently needed. This article, based on our experience and relevant guidelines and research, introduces essential knowledge about COVID-19 and nosocomial infection in dental settings and provides recommended management protocols for dental practitioners and students in (potentially) affected areas.

scholarly journals Research on the Design of Government Affairs Platform in the Context of Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qian Huang ◽  
Xue Wen Li
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Learning Algorithm ◽  
The Internet ◽  
Chinese Government ◽  
Development Status ◽  
Deep Learning Algorithm ◽  
Government Management ◽  
The Government ◽  
The Impact

Big data is a massive and diverse form of unstructured data, which needs proper analysis and management. It is another great technological revolution after the Internet, the Internet of Things, and cloud computing. This paper firstly studies the related concepts and basic theories as the origin of research. Secondly, it analyzes in depth the problems and challenges faced by Chinese government management under the impact of big data. Again, we explore the opportunities that big data brings to government management in terms of management efficiency, administrative capacity, and public services and believe that governments should seize opportunities to make changes. Brainlike computing attempts to simulate the structure and information processing process of biological neural network. This paper firstly analyzes the development status of e-government at home and abroad, studies the service-oriented architecture (SOA) and web services technology, deeply studies the e-government and SOA theory, and discusses this based on the development status of e-government in a certain region. Then, the deep learning algorithm is used to construct the monitoring platform to monitor the government behavior in real time, and the deep learning algorithm is used to conduct in-depth mining to analyze the government's intention behavior.

scholarly journals A PIECEWISE GROWTH MODEL FOR MODELING THE ACCUMULATED NUMBER OF COVID-19 CASES IN THE CITY OF CAMPO GRANDE

2021 ◽  
Vol 39 (1) ◽  
pp. 240
Author(s):  
Erlandson Ferreira SARAIVA ◽  
Leandro SAUER ◽  
Basílio De Bragança PEREIRA ◽  
Carlos Alberto de Bragança PEREIRA
Keyword(s):  
Growth Model ◽  
Health Department ◽  
World Health ◽  
Mathematical Study ◽  
Number Of Patients ◽  
Technical Report ◽  
The World ◽  
The Government ◽  
Health Organization ◽  
The City

In December of 2019, a new coronavirus was discovered in the city of Wuhan, China. The World Health Organization officially named this coronavirus as COVID-19. Since its discovery, the virus has spread rapidly around the world and is currently one of the main health problems, causing an enormous social and economic burden. Due to this, there is a great interest in mathematical models capable of projecting the evolution of the disease in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agents in making decisions in relation to the prevention of the disease. By using this argument, the health department of the city (HDC) of Campo Grande asked the UFMS for the development of a mathematical study to project the evolution of the disease in the city. In this paper, we describe a modeling procedure used to fit a piecewise growth model for the accumulated number of cases recorded in the city. From the fitted model, we estimate the date in which the pandemic peak is reached and project the number of patients who will need treatment in intensive care units. Weekly, was sent to HDC a technical report describing the main results.

scholarly journals Penggunaan Aplikasi Google Classroom sebagai Metode Pembelajaran Daring Selama Pandemi Covid-19

2021 ◽  
Vol 14 (2) ◽  
pp. 11-17
Author(s):  
Mirza Ghulamudin Ghulamudin ◽  
Maufur ◽  
Beni Habibi
Keyword(s):  
Distance Learning ◽  
World Health ◽  
Ministry Of Education ◽  
Health Crisis ◽  
Use Of Technology ◽  
The World ◽  
Teachers And Students ◽  
The Government ◽  
Health Organization ◽  
In The Beginning

Covid-19 has now attacked Indonesia, where the spread of the disease is very fast. Not only in Indonesia, but all corners of the world are currently experiencing a health crisis. In the beginning, the spread of Covid-19 had an impact on economic activity which began to sluggish. This also has an impact on the education system in Indonesia. Until several countries decided to close schools and universities. In an effort to prevent the spread of covid-19, the World Health Organization (WHO) recommends temporarily stopping activities that would potentially cause crowds. Even during the outbreak, covid-19 in Indonesia, there were many ways that the government did to prevent its spread through social distancing. Kemendikbud instructed through the Ministry of Education and Culture (Kemendikbud) Directorate of Higher Education Circular No. 1 of 2020 concerning the prevention of the spread of covid-19 in the world of Education to organize distance learning and advise students to learn from their homes. Teachers and students are starting to be required to follow the current situation by using technology as a distance learning medium. One of the media that is being favored by teachers as a learning medium is the Google Classroom application. This application is an application that can make it easier for students and teachers to create effective learning. Given that students today are a generation who are very familiar with the use of technology. The use of technology in learning is an alternative method used by teachers during the Covid-19 Pandemic.

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