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Can new technologies such as AI, big data, blockchain, 5G, etc. help us solve the problems caused by COVID-19?

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Over the last thousand years, mankind has experienced no less than ten extremely devastating epidemics, the last of which broke out about 100 years ago. And each time the most effective measures of protection against an unknown infection were quarantine measures: self-isolation, social distance, termination of transport between settlements. It is true that in the Middle Ages few people understood the ways of transmission, and the devastating disease was explained by the movement of celestial bodies, the burden of sins, or even a curse on the part of other people or nations.

Much later, masks and respirators for respiratory protection, gloves, and suits for skin protection, disinfectants, etc. were added to the protective equipment. Of course, today science has made a giant leap in the fight against viruses. Advances in microbiology, neurobiology, genetic engineering, regenerative medicine, and synthetic biology are hard to dispute. However, with the onset of the 2019-nCoV coronavirus pandemic, technologies that either did not exist or could hardly be called medical began to be used en masse to combat it 10 years ago. These include artificial intelligence, blockchain, 3D printing, robots, and drones.

This question was followed up by Allen Rast, the essay writer at Essaywriteronline.co

Artificial intelligence and big data
On December 30, 2019, the artificial intelligence program BlueDot, created by a Canadian startup of the same name, warned of a possible danger caused by an unknown virus in China. On the same evening, the Wuhan Health Department officially announced the discovery of a new disease. But the WHO announced it only nine days later.

The BlueDot system processes texts from hundreds of thousands of sources and thus builds its predictions. This is not the first time BlueDot has predicted epidemics. For example, in 2014 the program predicted the expansion of Ebola in Africa, and in 2016 the system managed to predict the Zika outbreak in Florida six months before the event itself.

By the way, BlueDot is not the only one - the automated HealthMap service at Boston Children's Hospital also detected the first signs of a pandemic before the official WHO reports. A mathematical model from Metabiota, a San Francisco startup, showed a similar result.

Two months later, a team of researchers from Wuhan demonstrated an innovative deep machine learning-based system that detects COVID-19 from a CT image with 95% accuracy. The model was trained on more than 45,000 CT images.

Another deep machine learning-based system has shown the ability to predict the survival rate of patients with severe COVID-19 with more than 90% accuracy.

But this is not the only application of AI-based solutions. For example, artificial intelligence and big data systems were used to monitor real-time changes in body temperature using wearable sensors. All this data was stacked in a single database and analyzed there. This made it possible to analyze the spread of new cases by region, to predict where the epidemic would spread more actively, and to assess and adjust the strategy to combat the epidemic.

Many IT vendors have been helping them to do just that. For example, in April 2020, HUAWEI CLOUD announced the launch of a global action plan aimed at combating COVID-19 through the cloud and AI services. As part of this plan, HUAWEI CLOUD will provide free artificial intelligence services and cloud services to partners around the world to jointly combat the pandemic.

However, these are not all the applications of AI during a pandemic. For example, artificial intelligence technologies were used to create new molecules that could serve as potential drugs or even reduce the time it takes to predict the secondary structure of the RNA of a virus.

Besides, AI-powered facial recognition technologies have tracked through video surveillance systems people who do not wear masks in public places or violate self-isolation. For example, Chinese Internet search giant Baidu has developed a facial recognition system that scans and takes photos of more than 200 people a minute at Beijing's Qinghe railway station.

Social networks began to adjust their AI-based filters to sift through information to find fake news. For example, YouTube started deleting all videos with fortune-tellers and all kinds of conspiracy theorists who broadcast anything about the spread of the coronavirus.

So why is the pandemic sweeping the world, despite the correct prognosis?
The fact that AI can detect an outbreak on the other side of the world before WHO even realizes it is really impressive because early warning can save lives. BlueDot's initial prediction correctly identified the cities where the virus would spread first, seemingly giving authorities a chance to prepare for the epidemic. But it wasn't all that simple. First, not everyone heard BlueDot's message and those who didn't necessarily take it seriously. Second, as the epidemic grew in scope, the predictions became less concrete and less accurate. The reason for this was that the news sources themselves also became increasingly contradictory. Official reports, media news, and the thoughts of experts and bloggers differed widely from one another. The authorities usually gave understated figures, the media tried to calculate the number of patients according to their formulas, and bloggers and fake experts sometimes inflated the most fantastic rumors. Information noise and misinformation are the enemies of machine learning algorithms.

Indeed, daily forecasts for BlueDot and Metabiota were easier to make in the first two or three weeks after the outbreak, not during the height of the epidemic.

So can we rely on the prediction of epidemiological cataclysms?
So far, we have seen how "noise" in the sources of information leads to errors in predictions. And the level of "noise" rises especially when we are dealing with something unknown and poorly studied. For example, many people infected with coronavirus had the disease without symptoms and did not make it into the statistics. Also, problems arose because doctors could not correctly identify COVID-19 until the diagnostic technology was perfected.

Is there a solution to this problem? Yes, many experts see the solution in the establishment of a global system of sharing anonymous data on cases of various diseases in each country, as well as improving machine learning methods that allow you to train models even on a small amount of information. It is known that in most countries of the world, data on patient referrals are already accumulated in the databases of hospitals, health ministries, etc. However, there is no external access to this information, because it is confidential. The goal for the coming years is to have the OIE and other organizations anonymize this data and collect it regularly on a newly created global data exchange platform. By being able to collect real statistics from around the world, AI will be able to more accurately predict outbreaks of dangerous diseases, which will benefit all of humanity.

Artificial intelligence is one of the most promising technologies in medicine. But others are directly related to IT (IT).

The use of blockchain would seem to have little to do with the coronavirus pandemic. But in reality, the technology has served the supply chain management industry well, as a study by the European Parliamentary Research Service points out.

It was on the blockchain that a platform was launched in February of this year, allowing users to track demand and supply chains for medical supplies, identify shortages of certain items, and solve problems related to the distribution and delivery of relief items.

When it comes to fundraisers, blockchain has allowed donors to monitor where their funds are needed, receive notifications when donations are received, and then monitor the use of donations.

Also, it is on the blockchain that Ant Financial's online mutual aid platform, Xiang Hu Bao, is built. The platform collectively accepts and processes coronavirus insurance claims, reduces paperwork, and allows all parties to control the process.

Telemedicine technologies
Of course, telemedicine was in use long before the Covid-19 epidemic. But the pandemic has shown that such technology is very effective in keeping doctors away from infection because it allows them to examine and diagnose patients remotely using a real-time audio-visual system.

The remote provision of medical care services provides several important benefits at once. Firstly, it reduces the rate at which the virus spreads, since there is no physical contact with a possible patient; secondly, a physician can treat a greater number of patients than would be possible with an in-person examination; and thirdly, telemedicine allows the treatment of patients in remote geographic locations that do not normally have access to highly qualified medical care. Besides, remote diagnosis makes it possible to determine immediately which patients can be admitted to the hospital and which can be left at home.

3D printing
3D printing has been used successfully for decades to quickly create unique prototypes of products in single copies. During the Covid-19 pandemic, these 3D printing capabilities were used en masse to produce ventilation valves, breathing filters, face mask clips, and even special foot adapters for plastic doorknobs that allowed you to open the door with your knee and not touch the door with your hands.

In Italy, a group of volunteers used their 3D printer to produce a batch of unofficial copies of a patented breathing apparatus valve. Also, several volunteers in various countries printed protective face shields for doctors performing Covid-19 tests, and in China, more than 5,000 pairs of protective glasses were printed daily for infectious disease doctors.

The main advantage of drones is their ability to perform various tasks without involving humans. Thus, medical workers could be shielded from hot zones. For example, drones were used to deliver consumer goods and medical samples to remote areas of the country, greatly reducing human-to-human contact.

Japanese industrial drone manufacturer Terra Drone began piloting its drones in China during an epidemic. The drones, which were originally designed to spray pesticides over fields, have been adapted to spray disinfectants in public places and transport goods between isolated areas. Police have also been known to use drones equipped with thermal sensors, night-vision cameras, high-resolution zoom lenses, and loudspeakers to identify pedestrians with fever, people in public places without masks, and restrict their movement.

Performing monotonous or dirty work in hard-to-reach or dangerous places has long been a familiar and familiar role for robots. Therefore, during the pandemic, robots were used en masse to minimize contact between medical personnel and other workers and infected people. For example, Panasonic Corporation suggested using autonomous robots HOSPI to sanitize "dirty" areas of medical institutions. By independently moving around the premises, the robot sprays special disinfectants.

In early March, a coronavirus field hospital unit opened in Wuhan, with robots performing such tasks as measuring patients' temperatures, delivering food, and disinfecting the facility.

The robots were also used in a hospital in Shenzhen that specializes in treating patients with Covid-19. Here, they were used to provide videoconferencing services for patients and doctors, as well as to monitor the body temperature of visitors and patients. A bacteria-killing robot called GermFalcon, designed to disinfect planes is currently being used at Los Angeles, San Francisco, and John F. Kennedy International Airports as an emergency response tool.

There are also service robots that can remotely measure body temperature, distribute hygiene items in each room, ask residents to wash their hands regularly, or simply remind them of their meal schedule.

Summary: What do we expect from new technologies?
The COVID-19 pandemic has become a driver for the increased use of innovative IT technologies in medicine. In a matter of months, many different advanced developments have appeared in the world and begun to be used en masse to fighting the coronavirus. Undoubtedly, even if the pandemic were to end tomorrow, the movement in this direction would continue. We should expect the widespread use of robots in hospitals, especially in infectious disease departments, and the increased use of telemedicine, which will also protect doctors from infection.

Particular hopes are pinned on artificial intelligence, machine learning, and big data analytics. First, because it will make it possible to predict the emergence and spread of epidemics of various diseases. Second, AI will help doctors diagnose diseases and perhaps, importantly, even protect against medical error. And third, artificial intelligence technology will help create new drugs. And humanity may meet the next global epidemic fully armed.

Biography of the author: Allen Rust, managing a restaurant before the pandemic and essay writer at Essaywriteronline.co now. He believes that all the changes in our life happen for the better.
Author: Allen Rust