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WASHINGTON: US health and technology specialists on March 16 said they had launched a new collaborative venture to assemble a dataset of tens of thousands of scientific papers and literature on the coronavirus, which would then be analysed by artificial intelligence programs to find patterns and answer questions raised by the World Health Organisation about the pandemic.

The dataset includes 29,000 articles, including 13,000 full-text pieces of medical literature, which will be made available on a special website allowing data scientists and artificial intelligence programmers to propose tools and software code that can unearth insights from the articles, White House officials and experts told reporters in a conference call.

The venture came together after the White House Office of Science and Technology Policy issued a call to tech companies and research groups to figure out how artificial intelligence tools could be used to sift through thousands of research articles being published worldwide on the pandemic, said Lynn Parker, deputy chief technology officer at the White House office.

With data scientists and machine language experts mining the literature compilation known as Covid-19 Open Research Dataset, experts and White House officials expect to get help developing vaccines, forming new guidelines on how long social distancing should be maintained and other insights, Michael Kratsios, the US chief technology officer said.

The venture includes the National Library of Medicine, which is part of the National Institutes of Health, Microsoft, Allen Institute of AI, Georgetown University's Center for Security and Emerging Technology, the Chan Zuckerberg Initiative (named for Mark Zuckerberg, Facebook's founder, and his wife Priscilla Chan), and Kaggle, which is a unit of Google.

The Allen Institute's Semantics Scholar website will host the database of scientific articles and add to the collection over time, while Kaggle's platform, which provides access to about 4 million artificial intelligence researchers, will receive suggestions from the experts on tools and codes to use to mine the database, experts from both organisations said.

Scientists have been working and publishing their findings on various strains of coronavirus over the years, including other variants such as SARS, MERS, and the latest, Covid-19. The application of artificial intelligence tools to look for commonalities and differences among the thousands of such published articles will help the scientists spot things they may have missed, Eric Horvitz, Microsoft's chief scientific officer said.

"It's difficult for people to manually go through more than 20,000 articles and synthesise their findings," Anthony Goldbloom, co-founder and CEO of Kaggle said. "Recent advances in technology can be helpful here. We're putting machine readable versions of these articles in front of our community of more than 4 million data scientists. Our hope is that AI can be used to help find answers to a key set of questions about Covid-19."

"Sharing vital information across scientific and medical communities is key to accelerating our ability to respond to the coronavirus pandemic," said Cori Bargmann, head of science at the Chan Zuckerberg Initiative. "The new Covid-19 Open Research Dataset will help researchers worldwide to access important information faster."

Publishers of scientific journals and literature have agreed to make their full articles available to researchers so that machine learning algorithms can look for key insights from them, the experts said. As scientists around the world continue to publish new research, journal publishers have agreed to provide those articles in electronic form ahead of their printed versions, they said. CQ-Roll Call/Tribune News Service

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Artificial intelligence recruited to find clues about Covid-19 - The Star Online

TUSTIN, Calif.--(BUSINESS WIRE)-- Canon Medical Systems USA, Inc. has received 510(k) clearance on its Advanced intelligent Clear-IQ Engine (AiCE) for the Vantage Galan 3T MR system, further expanding access to its new Deep Learning Reconstruction (DLR) technology. This technology, which is also available across a majority of Canon Medicals CT product portfolio, uses a deep learning algorithm to differentiate true MR signal from noise so that it can suppress noise while enhancing signal, forging a new frontier for MR image reconstruction.

AiCE was trained using vast amounts of high-quality image data, and features a deep learning neural network that can reduce noise and boost signal to quickly deliver sharp, clear and distinct images, further opening doors for advancements in MR imaging. Capabilities include:

AiCE utilizes a next generation approach to MR image reconstruction, further proving Canon Medicals leadership and commitment to innovation in diagnostic imaging, said Jonathan Furuyama, managing director, MR Business Unit, Canon Medical Systems USA, Inc. With the expansion of this unique DLR method across modalities and into MR, were elevating diagnostic imaging capabilities for our customers by bringing the power of AI to routine imaging to provide more possibilities in improving patient care than ever before.

About Canon Medical Systems USA, Inc.

Canon Medical Systems USA, Inc., headquartered in Tustin, Calif., markets, sells, distributes and services radiology and cardiovascular systems, including CT, MR, ultrasound, X-ray and interventional X-ray equipment. For more information, visit Canon Medical Systems website at https://us.medical.canon.

About Canon Medical Systems Corporation

Canon Medical offers a full range of diagnostic medical imaging solutions including CT, X-Ray, Ultrasound, Vascular and MR, as well as a full suite of Healthcare IT solutions, across the globe. In line with our continued Made for Life philosophy, patients are at the heart of everything we do. Our mission is to provide medical professionals with solutions that support their efforts in contributing to the health and wellbeing of patients worldwide. Our goal is to deliver optimum health opportunities for patients through uncompromised performance, comfort and safety features.

At Canon Medical, we work hand in hand with our partners - our medical, academic and research community. We build relationships based on transparency, trust and respect. Together as one, we strive to create industry-leading solutions that deliver an enriched quality of life. For more information, visit the Canon Medical website: https://global.medical.canon.

* AiCE MR is applicable to neuro and knee imaging

View source version on businesswire.com: https://www.businesswire.com/news/home/20200318005103/en/

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Canon Medical's 3T MR System Receives FDA Clearance for Artificial Intelligence-Based Image Reconstruction Technology - BioSpace

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Applying artificial intelligence to everything were comfortable doing in banking is much easier than changing how we do things which would make the greatest use of AI.

Few in financial services would argue that the future belongs to those institutions that harness data-driven machine intelligence to do more, better and faster. The insights and efficiencies needed to compete and thrive will come from AI-driven service personalization and optimization.

But AI should do more than speed up a financial assembly line. As Ernst & Young stated in a report: AI-driven financial health systems will become personal financial operating systems. Consumer finance will unbundle products and rebundle personalized and holistic value propositions based on life events.

While that is a worthy goal, the retail banking industry will not come any closer to achieving that if it continues the way it is thinking about and implementing AI.

I call the current mindset for applying AI to financial services the Product Gun. Its the familiar banking model of manufacturing a product, targeting a market segment for distribution, ensuring everything complies, and then shooting it to potential consumers. Its worked well for many years, but its had its day.

Hopes of providing consumers with personal financial operating systems and solutions tailored to life events wont happen merely by blending AI with the same old thing. In fact, applying complexity and leverage to well-understood financial products and processes may produce unintended consequences.

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But rethinking from the ground up can be rare. Models and the basic process behind them often dont change because business typically likes to save energy. Take the Boeing 737. The jets design dates back to 1964. The first one flew in 1967. The latest iteration still flies today. This makes a perfect example of leveraging an old business model to sustain profits as the saying goes, if it aint broke

Because banking is a regulated industry that deals with heaps of money and risk, a control structure has evolved to organize competencies and lines of business. Risk and profit are put in little boxes for success. Boxes like manufacture, target, and comply all have executives, KPIs, spreadsheets and politics. On the whole, it has worked well.

The problem is, innovative tools like AI get shoved into the same old boxes. Instead of using this technology to reimagine traditional processes, we use AI to build a supercharged 737.

This has some benefits to financial institutions business lines. This could include improving the consumer credit process, reducing compliance exceptions or automating support desks. Each of these, and similar applications of AI, could benefit the industry and those it serves.

However, AI can produce missteps, such as unwittingly biased outcomes. At best staying trapped inside old processes with new AI insides will do no harm, but its still not going to bring us closer to a vision for personalized, holistic financial advice.

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I want to propose something radical: Financial institutions should be optimizing for their clients needs. This sounds extremely simple but the commitment required, and the roadmap to making this reality is serious, expensive and difficult when it can take a long time to deliver on expectations.

Jeff Bezos said: Put the customer first. Invent. And be patient. It took Amazon 20 years to be profitable, and during that time Bezos kept investing to optimize his understanding of and delivery for his customers. Amazons impressive margins came about relatively recently, and only after a long battle.

The alternative to the traditional Product Gun attitude is something I call Mother Mind. This goes beyond simply shooting products at people. It gathers intelligence about what and who people are and what they need. It understands deeply what customers are going through in their lives, then it guides them with strategies that are actually going to be useful in the context of their lives. Used in this way, AI can keep guiding an institution in ways to better serve people and businesses.

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Change is hard for financial institutions, but it can happen. Here are three achievable pivots that can help put a bank or credit union on the path to success.

Gather: Move from system-centric data to human-centric data. Even under the progressive framework of Europes PSD2 open banking framework, financial institutions still store and access data in a system-centric way: transactions, products, accounts and balances. Data organized this way makes it very difficult to understand much about peoples individual circumstances.

Today data comes in the language of systems and ledgers. To do anything radically different requires shifting to the language of human lives. This means building interfaces to data that will allow financial institutions to ask questions about peoples behavior and needs. What are their financial personalities? What events in their lives offer the chance to be of assistance?

Understand: Move from products to journeys. The word customer-centric means nothing if products continue to be bankings foundation. How do we distribute the product for less? How do we recommend products to customers at the right time? such thinking is inverse, today.

Consumers needs change as their lives and circumstances change. At any point and time they have problems that need solutions and questions that need answers. Whether or not these journeys are successful is going to start meaning a lot more. Customer love or hate is going to be a profitability issue in a world where switching providers is easy. Focusing on understanding people will result in institutions working in a completely different way the measure wont be on sales but on problems resolved.

Guide: Move from selling to advising. By virtue of living in a product-centric world, financial institutions have become sales-driven. But when the barrier to entry to manufacturing and distributing products keeps lowering, traditional institutions increasingly find themselves fighting fintechs and others for turf they used to think they owned. Shiny objects may grab attention and move a sale once, but when thats over, if an institution hasnt built a meaningful relationship, people will leave.

People want to be understood, and they want to be cared for. In the context of financial services, this means people want advice. Advice is not about buying a product. Its about working towards goals, planning for transitions and hopefully creating an overarching, happy story of personal wealth.

Putting energy into human-centric data and focusing on understanding makes the aspiration of providing personalized holistic advice more possible.

The personal financial operating system wont happen overnight, but institutions can move towards it. Personal financial management offerings that keep people aware of their situation, tools that help them plan for retirement, and hybrid advice platforms that enable collaboration are all steps in the right direction.

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Rethinking Financial Services with Artificial Intelligence Tools - The Financial Brand

Using computers and machine learning to make sense of mountains of biomedical data is nothing new. But the team at the Massachusetts Institute of Technology, led by James Collins, who studies applications of systems biology to antibiotic resistance, and Regina Barzilay, an artificial-intelligence researcher, achieved success by developing a neural network that avoids scientists potentially limiting preconceptions about what to look for. Instead, the computer develops its own expertise.

Read: Antibiotic resistance is everyones problem

With this discovery platform, which has been made freely available, youre going to identify molecules that dont look like antibiotics youre used to seeing, Collins said. It really shows how you can use the emerging technology of deep learning in an innovative manner to discover new chemistries.

Ever since Alexander Fleming derived the first antibiotic from fungus, nature has been the font for our antibacterial drugs. But isolating, screening and synthesizing thousands of natural compounds for laboratory tests is extremely expensive and time-consuming.

To narrow the search, researchers have sought to understand how bacteria live and multiply, and then pursued compounds that attack those processes (such as by damaging bacterias cell walls, blocking their reproduction, or inhibiting their protein production). You start with the mechanisms, and then you reverse engineer the molecule, Barzilay said.

Even with the introduction of computer-assisted, high-throughput screening methods in the 1980s, however, progress in antibiotic development was virtually nonexistent in the decades that followed. Screening occasionally turned up drug candidates that were toxic to bacteria, but they were too similar to existing antibiotics to be effective against resistant bacteria. Pharmaceutical companies have since largely abandoned antibiotic development, despite the need, in favor of more lucrative drugs for chronic conditions.

Read: How antibiotic resistance could make common surgeries more dangerous

The new work by Barzilay, Collins, and their colleagues, however, takes a radically fresh, almost paradoxical approach to drug discovery: It ignores how the medicine works. Its an approach that can succeed only with the support of extremely powerful computing.

Behind the new antibiotic finding is a deep neural network, in which the nodes and connections of its learning architecture are inspired by the interconnected neurons in the brain. Neural networks, which are adept at recognizing patterns, are deployed across various industries and consumer technologies for uses such as image and speech recognition. Conventional computer programs might screen a library of molecules to find certain defined chemical structures, but neural networks can be trained to learn for themselves which structural signatures might be usefuland then find them.

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An Unexpected Ally in the War With Bacteria - The Atlantic

By Victor Bwire

Its during such times like the current corona virus outbreak that we ask our ourselves hard questions including how can innovations especially Artificial Intelligence (AI), help us deal with improve our responses and handling of such challenges.

Elsewhere it has been shown what AI and machine automated applications can do several things previously done by human; from smart cities, to facial recognition not the basic on your phone, but cameras that can detect that you have been to four malls in the city within the past one week and recognize your face when you are exiting at the airport to fully automated sales points and ticketing centers.

AI-powered tracking and warning systems, intensive observation methodologies and testing can be of huge importance to the country in the war on the corona virus.

Availability of government-run big-data platforms such CCTVs and others stores information of all citizens and foreign nationals and integrates all these for use. With such information, its easier to track those whom s/he had met during that time, and bring them under observation and medical tests.

AIe ensures prompt execution of all these steps. Hospitals, ambulance services, mobile test labs all rely on IT sector and technology to deliver prompt and efficient services.

Outside its negative side, would the implementation of the huduma number in time have been useful to the country in dealing with the current corona virus, especially in tracking down possible suspects, those self isolating and travel history of people- through obviously the issue of individual privacy has been raised before.

There have been previous innovations where technological applications and mobile phones have been used to tracking and offering health services to malaria patients and reproductive health services to teens.

Tech giants including Google, Facebook, Huawei through their various applications have been working over night elsewhere to support the dealing of the corona virus outbreak. Hopefully, Kenya, which has the presence of such big techs will eventually benefit from such technological innovation.

Today while reading an article by Eunice Kilinzo online, technology and medical services, my mind went to the many other stories I have read relating to technological innovations including mobile phone applications that have helped in enhancing the delivery of health services to Kenyans. Kilonzo talks about Ada a mobile application that uses artificial intelligence (AI) to track symptoms to get to the probable cause of an ailment.

The app, developed by Ada Health, a Germany-based health tech company, combines a database for 160 different diseases with intelligent reasoning technology.

Its reported that South Korea is fighting the virus by using big-data analysis, AI-powered advance warning systems and intensive observation methodology-the government-run big-data platform stores information of all citizens and resident foreign nationals and integrates all government organisations, hospitals, financial services, mobile operators, and other services into it, which is then integrated and used.

Huawei who are behind the 5G technology and working with Safaricom, who you be assisting Kenya in coming with applications through mobile phones to in mapping out and alerting health providers about the epicenters. Mobile phone operators safaricom and airtel have already reduced and or removed charges on their money transfer services.

I know Huawei since January started on a work from home service, office cleaning, social distance disinfecting office vehicles, employee shuttle buses and checking every employees and guests temperature, ensuring that all staff who had travelled from any country with any cases have been undergoing 14 days self-isolation and requiring all employees submit daily survey to confirm their health and those of their family in case they need support from us.

The bigger assignment I would expect from them is to scale up management of the critical telecommunications infrastructure and IT systems for government as well as telecommunications companies, which is the back borne of the countrys public awareness, information sharing and money transfer services.

Huawei must ensure that all telecoms systems function and can handle the current cashless economy we are dealing with because of the outbreak including working with Safaricom for M-PESA as well as other critical hardware and software.

I belong to a group started by facebook called Coronavirustechhandbook.com, where guys are posting innovations and efforts by tech experts and companies to make a contribution to the handling of the outbreak. For example, http://www.trackmycircle.com site where you log your contacts and you will be notified by email when a peer (or 3rd degree) is found COVID-19 positive so that you can self-isolate. Another interesting innovation is on http://www.worldmeters.info

With such big technology giants like Google, Facebook, IBM and other having AL research hubs across the continent, we expect technology to play a big roe in dealing with the corona virus on the continent.

Could we see AI-powered drones used in the tracking and monitoring and identification of cases and related interventions in combating the outbreak? We want to see players like the media using technology like skype, google recorders and related audio applications to carry out interviews and bring is news without necessarily attending face-to- face interviews and reporting to newsrooms.

Can those in charge of dissemination of information consider doing multimedia messages that can be shared across the country including with community and locally based journalists to help in public education.

Bwire is the Head of Media Development and Strategy at the Media Council of Kenya

Video Of The Day: PSA: How to protect yourself and others from Coronavirus

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