Futuristic Trends In European Health Insurance: Ai, Robotics, And Beyond

Futuristic Trends In European Health Insurance: Ai, Robotics, And Beyond – By Imtiaz Adam Machine and Deep Learning Engineer, DLS, MS Computer Science, Sloan Fellow in Strategy LBS, @ Deeplearn007

The outbreak of Coronavirus, or Covid-19, with lost or damaged lives and as a result of the economic crisis has highlighted the need for repair or maintenance of health and wellness systems around the world. Digital health care will become increasingly important in the future and hopefully lessons will be learned from the current crisis to mitigate and prevent similar futures.

Futuristic Trends In European Health Insurance: Ai, Robotics, And Beyond

The ways in which AI (Machine Learning and Deep Learning) technologies can be applied in the fight against Covid-19 include:

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The BBC notes in an article by Jane Wakefield that “Coronavirus: AI is stepping up the fight against Covid-19” and that the discovery of the drug has been slow.

“I have been doing this for 45 years and I have received three drugs for the market,” the article quotes AI co-founder and president of Discover Healx.

“It took weeks to gather all the data we needed and we’re been up to date in the last few days, so now we are at a critical juncture,” said Dr. Brown. .

The article further notes that AI can play a supportive role with other approaches. Scipher Medicine, for example, combines AI with what it calls network medicine, a method that looks at disease through complex interactions among molecular components.

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“The phenotype of the disease is rare due to the abnormal functioning of one gene or protein on its own, not naturally, but as a result of cascading effects in a network of interactions between multiple proteins,” Saleh said.

The use of AI network drugs and a combination of the two has led to companies identifying 81 potential drugs that could help.

The World Economic Forum in an article written by Swami Sivasubramanian and entitled “How AI and Machine Learning Are Helping to Fight COVID-19” Explains How AI plays an important role in understanding how Virus spread

Researchers at Chan Zuckerberg Biohubin California have developed a model to estimate the number of undiagnosed COVID-19 infections and their consequences for public health by analyzing 12 regions around the world using machine learning and capture. In partnership with the AWS Diagnostic Development Initiative, they have developed a new method to quantify undiagnosed infections – an analysis of how the virus changes as it spreads through the population to infer how many infections have been transmitted. Missed.

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At the outset of the epidemic, BlueDot, a Canadian startup and AWS client using AI to detect outbreaks, was the first to raise alarming alarms. Respiratory diseases in Wuhan, China.BlueDot uses AI to detect outbreaks. Using their machine learning algorithms, BlueDot passes news reports in 65 languages, along with carrier data and animal disease networks to find out. Epidemiologists then review the results and verify that the conclusions make sense from a scientific point of view. BlueDot provides those insights to public health officials, airlines and hospitals. Help them better anticipate and manage risks.

In addition, an article posted in the WEF notes the role of AI in drug detection and notes the work of Benevolent AI with Baricitinib, which is reportedly in the final stages of testing. Kaitlyn D’Onofrio reported on September 16, 2020 that Baricitinib Plus Remdesivir may reduce the recovery time of COVID-19.

An article by Tiernan Rayauthor entitled “MIT’s machine learning designed the COVID-19 vaccine that can cover most people” and noted that “not all vaccines for COVID-19 will cover everyone. There are big gaps. – The MIT machine learning project is designed to protect more people. “

It is understandable that many would ask that all work would go into developing a treatment and a potential vaccine, why is it unreliable and leaking material related to the disease?

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One major hurdle is the clinical trial phase. It makes sense to carefully test and evaluate potential drugs and vaccines for adverse effects and to ensure that they actually provide the required benefits. Unfortunately, this process will take time. However, CBINSIGHTS observed in an article entitled “The Future of Clinical Trials: How AI & Big Tech Can Make Drug Development Cheaper, Faster and More Effective.”

“Testing new drugs is slow, expensive, and manual. Artificial intelligence has the potential to disrupt all stages of the clinical trial process – from matching eligible patients to studying to adherence monitoring. And data collection. “

“This process is ineffective for other stakeholders too: drug tests, on average, last nearly a decade, costing billions of dollars. Many trials failed due to registration issues.”

Compared to other areas of healthcare, fewer startups are targeting clients directly in clinical trials. And in many aspects of clinical trials there is a need

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“As discussed above, many tests still rely on paper logs for data. These diaries are often stored digitally in hard-to-find formats, while handwritten notes pose special challenges for “Natural language processing algorithms to retrieve information.”

“One of the biggest hurdles in clinical trials will be overcoming inertia to fix current processes that no longer work.”

We are saddened to see the second wave of Covid-19 emerging around the world, and some countries have never emerged from their first wave.

It is too late to change the system for this particular crisis. One hopes that we will have safe and effective vaccines and other effective treatments available in early 2021. One also hopes that the legacy of this health crisis will result in an economic crisis for our political leaders to understand the need to launch digital transformation and health care reform.

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This article will focus on the impact of AI, 5G, Edge Computing on the healthcare sector by 2020, as well as a section on the potential impact of Quantum Computing on AI, healthcare and financial services. The next series will talk about how we can use AI to combat climate change, including protecting Amazon, smart cities and AGI.

For those who are new to AI, Machine Learning and Deep Learning, I recommend looking at the article below entitled “Introduction to AI”. I will refer to Machine Learning and Deep Learning as subdivisions of AI. In addition, this article is not exhaustive regarding the potential application of AI on healthcare and Quantum Computing to various sectors of the economy.

The reason for focusing on AI in health care is based on recent articles by some senior physicians in the United States that raise concerns about the role of AI in health care.

Some of the concerns raised, such as the need for improved data sharing by healthcare participants, including hospitals, and the highest quality assurance in data management, are completely correct, and I understand the need for data access. And data sharing by hospitals. Probably a matter of political and regulatory concern. In addition to a careful assessment of the facts, the basis for data labeling, testing and validation of samples needs to be guaranteed across all AI companies providing services throughout healthcare.

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However, I still hold the view that AI and especially Deep Learning technology will play an important role in health care by 2020.

In addition, it is important to note that the current medical system is broken and the system is getting worse. I expect health care to be a major issue in the 2020 US presidential election and also to be expected in the UK. For example, Robert Pearl observed that “health care is still a matter of national abstinence before the 2020 elections … Surveyors are still frustrated with high drug prices, rising costs. Out of pocket and endless health insurance benefits. “

On a personal level, I am obsessed with the potential for AI in healthcare throughout the next decade. The projects I have been involved in health care involve working with a team of professionals from the field of highly qualified medical practitioners (PhD research level) postgraduate in biology, computation, biochemistry and physics, along with machine experts. Learning. The group has both men and women and different cultural backgrounds, which allows for higher performance groups.

Moreover, I believe that such cross-border skills are essential for the successful discovery of drugs and personal medicine projects. Domain experience is necessary to propose technical solutions. However, we can often find that solutions to problems often come from outside the realm. Jeff Bezos, for example, shifted from finance to retail, and Elon Must’s record for disrupting various sectors. It is clear to those who have used the health care system that there is a real problem and that it needs to be addressed. Finding solutions for health care by combining a diverse background with knowledge of the health care system, along with AI experts who can assess issues with different perspectives, can help address issues in the healthcare sector.

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In 2020, we will see the integration of emerging technologies with AI is at the heart of it all.

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