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Digital technology and COVID-19 - Nature Medicine

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First, the IoT provides a platform that allows public-health agencies access to data for monitoring the COVID-19 pandemic. For example, the'Worldometer' provides a real-time update on the actual number of people known to have COVID-19 worldwide, including daily new cases of the disease, disease distribution by countries and severity of disease (recovered, critical condition or death) (https://www.worldometers.info/coronavirus/). Second, big data also provides opportunities for performing modeling studies of viral activity and for guiding individual country healthcare policymakers to enhance preparation for the outbreak. Using three global databases―the Official Aviation Guide, the location-based services of the Tencent (Shenzhen, China), and the Wuhan Municipal Transportation Management Bureau―Wu et al. performed a modeled study of'nowcasting' and forecasting COVID-19 disease activity within and outside China that could be used by the health authorities for public-health planning and control worldwide8. Similarly, using the WHO International Health Regulations, the State Parties Self-Assessment Annual Reporting Tool, Joint External Evaluation reports and the Infectious Disease Vulnerability Index, Gilbert et al. assessed the preparedness and vulnerability of African countries in battling against COVID-19; this would help raise awareness of the respective health authorities in Africa to better prepare for the viral outbreak9.


Is The Wheel Being Reinvented – The Paradigm Shift Of Ai From Bc (Before Carona) To Ac (After Corona) World

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Music and entertainment are among the fastest-growing industries today, globally and in India. Digital media and the internet have broken down the geographical boundaries, making the entire global population a potential audience to music and entertainment. On December 30, 2019, an AI-driven health monitoring platform called BlueDot spotted a cluster of unusual pneumonia cases occurring in Wuhan, China. The Canadian company sent out a warning to its customers the next day -- December 31. They had identified what would come to be known as COVID-19 a week before the Centre for Disease Control and Prevention (CDC) in USA or 2 weeks before WHO was able to spot it. Artificial Intelligence, or AI, has played a key role in identifying and addressing the pandemic.


Detection of COVID -- 19 using Deep Learning

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"Coronavirus disease 2019 (COVID-19) is a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2". "The disease first originated in December 2019 from Wuhan, China and since then it has spread globally across the world affecting more than 200 countries. The impact is such that the World Health Organization(WHO) has declared the ongoing pandemic of COVID-19 a Public Health Emergency of International Concern." As of 29th April, there are a total of 31,30,191 cases with 2,17,674 deaths in more than 200 countries across the world. So, in this particular scenario, one primary thing that needs to be done and has already started in the majority of the countries is Manual testing, so that the true situation can be understood and appropriate decisions can be taken.


AI Can Ease Path Towards Post-Pandemic Normality - Minutehack

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It's undeniable that the coronavirus pandemic has had an irreversible effect on virtually all facets of daily live, but with a clutch of countries now beginning to loosen Covid restrictions, there are hopes that the world may finally be emerging from the turmoil that has enveloped it over the last two years. It now makes sense for the global population to look towards a new semblance of normality – one that will be characterized by remarkable advances in artificial intelligence (AI), data science and other digital technology, which could provide significant assistance in keeping Covid, as well as any other viral diseases that may arise, under control. The merits of AI have already been amply displayed during the pandemic, with regard to its diagnostics, forecasting, drug development and screening capabilities. Moving forward, it's logical that it could provide similar succor in enabling to live with the virus – but without the existential anxiety that has accompanied it thus far. Just over two years since the discovery of the coronavirus outbreak in Wuhan, the virus may finally be in retreat.


Rand Paul seeking answers on COVID origins, gain-of-function research from 'convention of civilized countries'

FOX News

Fox News State Department correspondent Benjamin Hall reports on the murky world of gain of function research after the Wuhan Institute of Virology in China is suspected of starting the pandemic. FIRST ON FOX: Sen. Rand Paul, R-Ky., says he will advocate for an "international convention of civilized countries" to gather and discuss the dangers of gain-of-function research. Paul has been one of few leaders in Congress pressing for a hearing on the origins of COVID-19. The National Institutes of Health (NIH) last year acknowledged its efforts to fund gain-of-function research on bats infected with coronaviruses at a lab in Wuhan, China, before COVID-19 broke out and forever altered life around the world. "Not only do we need restrictions in our country," Paul told Fox News Digital in an interview of the research method.


COVID-19 detection in CT and CXR images using deep learning models - Biogerontology

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Infectious diseases pose a threat to human life and could affect the whole world in a very short time. Corona-2019 virus disease (COVID-19) is an example of such harmful diseases. COVID-19 is a pandemic of an emerging infectious disease, called coronavirus disease 2019 or COVID-19, caused by the coronavirus SARS-CoV-2, which first appeared in December 2019 in Wuhan, China, before spreading around the world on a very large scale. The continued rise in the number of positive COVID-19 cases has disrupted the health care system in many countries, creating a lot of stress for governing bodies around the world, hence the need for a rapid way to identify cases of this disease. Medical imaging is a widely accepted technique for early detection and diagnosis of the disease which includes different techniques such as Chest X-ray (CXR), Computed Tomography (CT) scan, etc.


COVID-19 detection in CT and CXR images using deep learning models

#artificialintelligence

Infectious diseases pose a threat to human life and could affect the whole world in a very short time. Corona-2019 virus disease (COVID-19) is an example of such harmful diseases. COVID-19 is a pandemic of an emerging infectious disease, called coronavirus disease 2019 or COVID-19, caused by the coronavirus SARS-CoV-2, which first appeared in December 2019 in Wuhan, China, before spreading around the world on a very large scale. The continued rise in the number of positive COVID-19 cases has disrupted the health care system in many countries, creating a lot of stress for governing bodies around the world, hence the need for a rapid way to identify cases of this disease. Medical imaging is a widely accepted technique for early detection and diagnosis of the disease which includes different techniques such as Chest X-ray (CXR), Computed Tomography (CT) scan, etc.


Fully Convolutional Change Detection Framework with Generative Adversarial Network for Unsupervised, Weakly Supervised and Regional Supervised Change Detection

arXiv.org Artificial Intelligence

Abstract--Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most endto-end networks are proposed for supervised change detection, and unsupervised change detection models depend on traditional pre-detection methods. Therefore, we proposed a fully convolutional change detection framework with generative adversarial network, to conclude unsupervised, weakly supervised, regional supervised, and fully supervised change detection tasks into one framework. A basic Unet segmentor is used to obtain change detection map, an image-to-image generator is implemented to model the spectral and spatial variation between multi-temporal images, and a discriminator for changed and unchanged is proposed for modeling the semantic changes in weakly and regional supervised change detection task. The iterative optimization of segmentor and generator can build an end-to-end network for unsupervised change detection, the adversarial process between segmentor and discriminator can provide the solutions for weakly and regional supervised change detection, the segmentor itself can be trained for fully supervised task. The experiments indicate the effectiveness of the propsed framework in unsupervised, weakly supervised and regional supervised change detection. This paper provides theorical definitions for unsupervised, weakly supervised and regional supervised change detection tasks, and shows great potentials in exploring end-to-end network for remote sensing change detection. It changes and non-changes by pre-detection, and use aims at finding landscape changes from the multi-temporal the corresponding patches as training samples to build a remote sensing images observing the same study site deep network model to extract better features and discriminate at different time. It has been widely used in land-use/landcover semantic labels [25-27].


Artificial intelligence -- saviour or monster?

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The years 2020 and 2021 have already been eclipsed by Covid-19. As we enter 2022, the Omicron variant has risen, giving a sense of deja vu. The pandemic has, however, played a critical role in giving an accelerated impetus to use of technology in our lives. For instance, BlueDot, an artificial intelligence (AI) platform, was the first to flag an "unusual pneumonia" in Wuhan. AI has been enhancing our capabilities in ways never witnessed in the past.


'Gutfeld' on COVID warnings for New Year's Eve, 2021 in review

FOX News

'Gutfeld!' panel discusses the year in review as 2021 comes to a close. This is a rush transcript from "Gutfeld!," December 30, 2021. This copy may not be in its final form and may be updated. EMILY COMPAGNO, FOX NEWS CHANNEL HOST: I know what you're thinking. Greg's never looked at this good in a dress. Like a tiny Ghost of Christmas Present, because I'm celebrating the holiday today. Because this year COVID robbed me of Christmas with my family. COVID robbed us of our studio audience. And it robbed me of my Christmas Eve Feast of the Seven Fishes. So to make up for it, we are having a feast tonight. COMPAGNO: In New Year's Eve news, Omicron fear mongers are warning people to stay away from New York's Times Square celebration. Even though previous crowds were exposed to something much worse. Thank God it'll be me hosting in Time Square this year. See you at 10:00 p.m. Eastern on Fox News. Germany's also banned large group gatherings. But you know who's never bans large gatherings of Germans? China's Wuhan Institute of virology recently hosted a conference on lab safety, to which the world responded a little (BLEEP) late, guys. In a recent segment on COVID Safety, CNN's Dr. Leana Wen admitted cloth masks don't stop transmission of the virus. Today in New York Mayor Bill de Blasio said he doesn't believe in shutdowns despite having shut down the city for months. He then added "I also oppose letting criminals roam free to murder people." Chris Tucker turned down a $10 million payday for a sequel to the awesome movie Friday, saying he's too mature to be seen behaving badly on screen anymore.