Access to the online databases is free to qualified researchers and medical experts to help them identify a potential treatment for the novel coronavirus.

IBM Research is making multiple free resources available to help healthcare researchers, doctors, and scientists around the world accelerate COVID-19 drug discovery. The resources can help with gathering insights, to applying the latest virus genomic information and identifying potential targets for treatments, to creating new drug molecule candidates, the company said in a statement.Though some of the resources are still in exploratory stages, IBM is giving access to qualified researchers at no charge to aid the international scientific investigation of COVID-19.The announcement follows IBM's launch of the US COVID-19 High Performance Computing Consortium, which is harnessing massive computing power in the effort to help confront the coronavirus, the company said.

Healthcare agencies and governments around the world have quickly amassed medical and other relevant data about the pandemic. And, there are already vast troves of medical research that could prove relevant to COVID-19, IBM said."Yet, as with any large volume of disparate data sources, it is difficult to efficiently aggregate and analyze that data in ways that can yield scientific insights," the company said.SEE: How tech companies are fighting COVID-19 with AI, data and ingenuity (TechRepublic)

To help researchers access structured and unstructured data quickly, IBM has offered a cloud-based AI research resource that the company said has been trained on a corpus of thousands of scientific papers contained in the COVID-19 Open Research Dataset (CORD-19), prepared by the White House and a coalition of research groups, and licensed databases from the DrugBank, Clinicaltrials.gov and GenBank.

"This tool uses our advanced AI and allows researchers to pose specific queries to the collections of papers and to extract critical COVID-19 knowledge quickly," the company said. However, access to this resource will be granted only to qualified researchers, IBM said.

The traditional drug discovery pipeline relies on a library of compounds that are screened, improved, and tested to determine safety and efficacy, IBM noted.

"In dealing with new pathogens such as SARS-CoV-2, there is the potential to enhance the compound libraries with additional novel compounds," the company said. "To help address this need, IBM Research has recently created a new, AI-generative framework which can rapidly identify novel peptides, proteins, drug candidates and materials."

This AI technology has been applied against three COVID-19 targets to identify 3,000 new small molecules as potential COVID-19 therapeutic candidates, the company said. IBM is releasing these molecules under an open license, and researchers can study them via a new interactive molecular explorer tool to understand their characteristics and relationship to COVID-19 and identify candidates that might have desirable properties to be further pursued in drug development.To streamline efforts to identify new treatments for COVID-19, IBM said it is also making the IBM Functional Genomics Platform available for free for the duration of the pandemic."Built to discover the molecular features in viral and bacterial genomes, this cloud-based repository and research tool includes genes, proteins and other molecular targets from sequenced viral and bacterial organisms in one place with connections pre-computed to help accelerate discovery of molecular targets required for drug design, test development and treatment," IBM said.

Select IBM collaborators from government agencies, academic institutions and other organizations already use this platform for bacterial genomic study, according to IBM. Now, those working on COVID-19 can request the IBM Functional Genomics Platform interface to explore the genomic features of the virus.

Clinicians and healthcare professionals on the frontlines of care will also have free access to hundreds of pieces of evidence-based, curated COVID-19 and infectious disease content from IBM Micromedex and EBSCO DynaMed, the company said.

These two decision support solutions will give users access to drug and disease information in a single and comprehensive search, according to IBM. Clinicians can also provide patients with consumer-friendly education handouts with relevant, actionable medical information, the company said.IBM's Micromedex online reference databases provide medication information that is used by more than 4,500 hospitals and health systems worldwide, according to IBM."The scientific community is working hard to make important new discoveries relevant to the treatment of COVID-19, and we're hopeful that releasing these novel tools will help accelerate this global effort," the company said."This work also outlines our long-term vision for the future of accelerated discovery, where multi-disciplinary scientists and clinicians work together to rapidly and effectively create next generation therapeutics, aided by novel AI-powered technologies."

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IBM Research releases a new set of cloud- and artificial intelligence-based COVID-19 resources - TechRepublic

Clinicians and researchers at Stanford University are developing ways that artificial intelligence can help identify which patients will require intensive care amid a surge in coronavirus patients. Rather than build an algorithm from scratch, the goal by Stanford experts was to take existing technology and modify it for a seamless transition into clinical operations.

The hardest part, the most important part of this work is not the model development. But its the workflow design, the change management, figuring out how do you develop that system the model enables, said Ron Li, a Stanford physician, and clinical informaticist.

Per a STAT news report, the machine learning model Lis team is working with analyzes patients data and assigns them a score based on how sick they are and how likely they are to need escalated care. If the algorithm can be validated, Stanford plans to start using it to trigger clinical steps such as prompting a nurse to check in more frequently or order tests that would ultimately help physicians make decisions about a COVID-19 patients care.

As more technology flows into fighting the coronavirus pandemic, this can only open up opportunities for investors in healthcare-focused exchange-traded funds (ETFs).

ETF investors can look for opportunities in theHealth Care Select Sector SPDR ETF (NYSEArca: XLV),Vanguard Health Care ETF (NYSEArca: VHT)and theiShares US Medical Devices ETF (IHI).

XLV seeks investment results that correspond generally to the Health Care Select Sector Index. The index includes companies from the following industries: pharmaceuticals; health care equipment & supplies; health care providers & services; biotechnology; life sciences tools & services; and health care technology.

VHT employs an indexing investment approach designed to track the performance of the MSCI US Investable Market Index (IMI)/Health Care 25/50, an index made up of stocks of large, mid-size, and small U.S. companies within the health care sector, as classified under the Global Industry Classification Standard (GICS).

IHI seeks to track the investment results of the Dow Jones U.S. Select Medical Equipment Index composed of U.S. equities in the medical devices sector. The underlying index includes medical equipment companies, including manufacturers and distributors of medical devices such as magnetic resonance imaging (MRI) scanners, prosthetics, pacemakers, X-ray machines, and other non-disposable medical devices.

Another fund to consider is theRobo Global Healthcare Technology and Innovation ETF (HTEC). HTEC seeks to provide investment results that, before fees and expenses, correspond generally to the price and yield performance of the ROBO Global Healthcare Technology and Innovation Index.

The fund will normally invest at least 80 percent of its total assets in securities of the index or in depositary receipts representing securities of the index. The index is designed to measure the performance of companies that have a portion of their business and revenue derived from the field of healthcare technology, and the potential to grow within this space through innovation and market adoption of such companies, products and services.

For more market trends, visitETF Trends.

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Stanford is Using Artificial Intelligence to Help Treat Coronavirus Patients - ETF Trends

The coronavirus outbreak has rapidly accelerated the nations slow-moving effort to incorporate artificial intelligence into medical care, as hospitals grasp onto experimental technologies to relieve an unprecedented strain on their resources.

AI has become one of the first lines of defense in the pandemic. Hospitals are using it to help screen and triage patients and identify those most likely to develop severe symptoms. Theyre scanning faces to check temperatures and harnessing fitness tracker data, to zero in on individual cases and potential clusters. They are also using AI to keep tabs on the virus in their own communities. They need to know who has the disease, who is likely to get it, and what supplies are going to run out tomorrow, two weeks from now, and further down the road.

Just weeks ago, some of those efforts might have stirred a privacy backlash. Other AI tools were months from deployment because clinicians were still studying their impacts on patients. But as Covid-19 has snowballed into a global crisis, health cares normally methodical approach to new technology has been hijacked by demands that are plainly more pressing.

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Theres a crucial caveat: Its not clear if these AI tools are going to work. Many are based on drips of data, often from patients in China with severe disease. Those data might not be applicable to people in other places or with milder disease. Hospitals are testing models for Covid-19 care that were never intended to be used in such a scenario. Some AI systems could also be susceptible to overfitting, meaning that theyve modeled their training data so well that they have trouble analyzing new data which is coming in constantly as cases rise.

The uptake of new technologies is moving so fast that its hard to keep track of which AI tools are being deployed and how they are affecting care and hospital operations. STAT has developed a comprehensive guide to that work, broken down by how the tools are being used.

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This list focuses only on AI systems being used and developed to directly aid hospitals, clinicians, and patients. It doesnt cover the flurry of efforts to use AI to identify drug and vaccine candidates, or to track and forecast the spread of the virus.

This is one of the earliest and most common uses of AI. Hospitals have deployed an array of automated tools to allow patients to check their symptoms and get advice on what precautions to take and whether to seek care.

Some health systems, including Cleveland Clinic and OSF HealthCare of Illinois, have customized their own chatbots, while others are relying on symptom checkers built in partnership with Microsoft or startups such as Boston-based Buoy Health. Apple has also released its own Covid-19 screening system, created after consultation with the White House Coronavirus Task Force and public health authorities.

Developers code knowledge into those tools to deliver recommendations to patients. While nearly all of them are built using the CDCs guidelines, they vary widely in the questions they ask and the advice they deliver.

STAT reporters recently drilled eight different chatbots about the same set of symptoms. They produced confusing patchwork of responses. Some experts on AI have cautioned that these tools while well-intentioned are a poor substitute for a more detailed conversation with a clinician. And given the shifting knowledge-base surrounding Covid-19, these chatbots also require regular updates.

If you dont really know how good the tool is, its hard to understand if youre actually helping or hurting from a public health perspective.

Andrew Beam, artificial intelligence researcher

If you dont really know how good the tool is, its hard to understand if youre actually helping or hurting from a public health perspective, said Andrew Beam, an artificial intelligence researcher in the epidemiology department at Harvard T.H. Chan School of Public Health.

Clover, a San Francisco-based health insurance startup, is using an algorithm to identify its patients most at risk of contracting Covid-19 so that it can reach out to them proactively about potential symptoms and concerns. The algorithm uses three main sources of data: an existing algorithm the company uses to flag people at risk of hospital readmission, patients scores on a frailty index, and information on whether a patient has an existing condition puts them at a higher risk of dying from Covid-19.

AI could also be used to catch early symptoms of the illness in health care workers, who are at particularly high risk of contracting the virus. In San Francisco, researchers at the University of California are using wearable rings made by health tech company Oura to track health care workers vital signs for early indications of Covid-19. If those signs including elevated heart rate and increased temperature show up reliably on the rings, they could be fed into an algorithm that would give hospitals a heads-up about workers who need to be isolated or receive medical care.

Covid-19 testing is currently done by taking a sample from a throat or nasal swab and then looking for tiny snippets of the genetic code of the virus. But given severe shortages of those tests in many parts of the country, some AI researchers believe that algorithms could be used as an alternative.

Theyre using chest images, captured via X-rays or computed tomography (CT) scans, to build AI models. Some systems aim simply to recognize Covid-19; others aim to distinguish, say, a case of Covid-19-induced pneumonia from a case caused by other viruses or bacteria. However, those models rely on patients to be scanned with imaging equipment, which creates a contamination risk.

Other efforts to detect Covid-19 are sourcing training data in creative ways including by collecting the sound of coughs. An effort called Cough for the Cure led by a group of San Francisco-based researchers and engineers is asking people who have tested either negative or positive for Covid-19 to upload audio samples of their cough. Theyre trying to train a model to tell the difference, though its not clear yet that a Covid-19 cough has unique features.

Among the most urgent questions facing hospitals right now: Which of their Covid-19 patients are going to get worse, and how quickly will that happen? Researchers are racing to develop and validate predictive models that can answer those questions as rapidly as possible.

The latest algorithm comes from researchers at NYU Grossman School of Medicine, Columbia University, and two hospitals in Wenzou, China. In an article published in a computer science journal on Monday, the researchers reported that they had developed a model to predict whether patients would go on to develop acute respiratory distress syndrome or ARDS, a potentially deadly accumulation of fluid in the lungs. The researchers trained their model using data from 53 Covid-19 patients who were admitted to the Wenzhou hospitals. They found that the model was between 70% and 80% accurate in predicting whether the patients developed ARDS.

At Stanford, researchers are trying to validate an off-the-shelf AI tool to see if it can help identify which hospitalized patients may soon need to be transferred to the ICU. The model, built by the electronic health records vendor Epic, analyzes patients data and assigns them a score based on how sick they are and how likely they are to need escalated care. Stanford researchers are trying to validate the model which was trained on data from patients hospitalized for other conditions in dozens of Covid-19 patients. If it works, Stanford plans to use it as a decision-support tool in its network of hospitals and clinics.

Similar efforts are underway around the globe. In a paper posted to a preprint server that has not yet been peer-reviewed, researchers in Wuhan, China, reported that they had built models to try to predict which patients with mild Covid-19 would ultimately deteriorate. They trained their algorithms using data from 133 patients who were admitted to a hospital in Wuhan at the height of its outbreak earlier this year. And in Israel, the countrys largest hospital has deployed an AI model developed by the Israeli company EarlySense, which aims to predict which Covid-19 patients may experience respiratory failure or sepsis within the next six to eight hours.

AI is also helping to answer pressing questions about when hospitals might run out of beds, ventilators, and other resources. Definitive Healthcare and Esri, which makes mapping and spatial analytics software, have built a tool that measures hospital bed capacity across the U.S. It tracks the location and number of licensed beds and intensive care (ICU) beds, and shows the average utilization rate.

Using a flu surge model created by the CDC, Qventus is working with health systems around the country to predict when they will reach their breaking point. It has published a data visualization tracking how several metrics will change from week to week, including the number of patients on ventilators and in ICUs.

Its current projection: At peak, there will be a shortage of 9,100 ICU beds and 115,000 beds used for routine care.

To focus in-person resources on the sickest patients, many hospitals are deploying AI-driven technologies designed to monitor patients with Covid-19 and chronic conditions that require careful management. Some of these tools simply track symptoms and vital signs, and make limited use of AI. But others are designed to pull out trends in data to predict when patients are heading toward a potential crisis.

Mayo Clinic and the University of Pittsburgh Medical Center are working with Eko, the maker of a digital stethoscope and mobile EKG technology whose products can flag dangerous heart rhythm abnormalities and symptoms of Covid-19. Mayo is also teaming up with another mobile EKG company, AliveCor, to identify patients at risk of a potentially deadly heart problem associated with the use of hydroxychloroquine, a drug being evaluated for use in Covid-19.

Many developers of remote monitoring tools are scrambling to deploy them after the Food and Drug Administration published a new policy indicating it will not object to minor modifications in the use or functionality of approved products during the outbreak. That covers products such as electronic thermometers, pulse oximeters, and products designed to monitor blood pressure and respiration.

Among them is Biofourmis, a Boston-based company that developed a wearable that uses AI to flag physiological changes associated with the infection. Its product is being used to monitor Covid-19 patients in Hong Kong and three hospitals in the U.S. Current Health, which makes a similar technology, said orders from hospitals jumped 50% in a five-day span after the coronavirus began to spread widely in the U.S.

Several companies are exploring the use of AI-powered temperature monitors to remotely detect people with fevers and block them from entering public spaces. Tampa General Hospital in Florida recently implemented a screening system that includes thermal-scanning face cameras made by Orlando, Fla.-based company Care.ai. The cameras look for fevers, sweating, and discoloration. In Singapore, the nations health tech agency recently partnered with a startup called KroniKare to pilot the use of a similar device at its headquarters and at St. Andrews Community Hospital.

As experimental therapies are increasingly tested in Covid-19 patients, monitoring how theyre faring on those drugs may be the next frontier for AI systems.

A model could be trained to analyze the lung scans of patients enrolled in drug studies and determine whether those images show potential signs of improvement. That could be helpful for researchers and clinicians desperate for signal on whether a treatment is working. Its not clear yet, however, whether imaging is the most appropriate way to measure response to drugs that are being tried for the first time on patients.

This is part of a yearlong series of articles exploring the use of artificial intelligence in health care that is partly funded by a grant from the Commonwealth Fund.

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STAT's guide to how hospitals are using AI to fight Covid-19 - STAT

Scientists have developed an artificial intelligence system that can translate a persons thoughts into text by analysing their brain activity. Researchers at the University of California developed the AI to decipher up to 250 words in real-time from a set of between 30 and 50 sentences.The algorithm was trained using the neural signals of four women with electrodes implanted in their brains, which were already in place to monitor epileptic seizures. The volunteers repeatedly read sentences aloud while the researchers fed the brain data to the AI to unpick patterns that could be associated with individual words. The average word error rate across a repeated set was as low as 3%.'; var randomNumber = Math.random(); var isIndia = (window.geoinfo && window.geoinfo.CountryCode === 'IN') && (window.location.href.indexOf('outsideindia') === -1 ); console.log(isIndia && randomNumber A decade after speech was first decoded from human brain signals, accuracy and speed remain far below that of natural speech, states a paper detailing the research, published in the journal Nature Neuroscience. We trained a recurrent neural network to encode each sentence-length sequence of neural activity into an abstract representation, and then to decode this representation, word by word, into an English sentence, the report states.The system is, however, still a long way off being able to understand regular speech. People could become telepathic to some degree, able to converse not only without speaking but without words, the report stated.

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Artificial Intelligence turns a persons thoughts into text - Times of India

You have probably heard that artificial intelligence could be used to do lots of impressive tasks and jobs. AI can help designers and artists make quick tweaks to visuals. AI can also help researchers identify fake images or connect touch and sense. AI is being used to program websites and apps by combining symbolic reasoning and deep learning. Basically, artificial intelligence goes beyond deep learning. Here are five reasons why AI is important to you.

It is no news that AI will replace repetitive jobs. It literally means that these kinds of jobs will be automated, like what robots are currently doing in a myriad of factories. Robots are rendering the humans that are supposed to do those tasks practically jobless.

And it goes further than that many white collar tasks in the fields of law, hospitality, marketing, healthcare, accounting, and others are adversely affected. The situation seems scary because scientists are just scratching the surface as extensive research and development of AI. AI is advancing rapidly (and it is more accessible to everybody).

Some believe that AI can create even more new jobs than ever before. According to this school of thought, AI will be the most significant job engine the world has ever seen. Artificial intelligence will eliminate low-skilled jobs and effectively create massive high-skilled job opportunities that will span all sectors of the economy.

For example, if AI becomes fully adapt to language translation, it will create a considerable demand for high-skilled human translators. If the costs of essential translations drop to nearly zero, this will encourage MORE companies that need this particular service to expand their business operations abroad.

To those who speak different languages than the community in which they reside, this help will inevitably create more work for high-skilled translators, boost more economic activities. As a result of this, and more people will be employed in these companies due to the increased workload.

Boosting international trade it one of the most significant benefits of our global times. So yes, AI will eliminate some jobs, but it will create many, many more.

AI can be used extensively in the healthcare industry. It is applicable in automated operations, predictive diagnostics, preventive interventions, precision surgery, and a host of other clinical operations. Some individuals predict that AI will completelyreshape the healthcare landscape for the better.

And here are some of the applications of artificial intelligence in healthcare:

AI is also used in the agriculture industry extensively. Robots can be used to plant seeds, fertilized crops and administer pesticides, among a lot of other uses. Farmers can use a drone to monitor the cultivation of crops and also collect data for analysis.

The value-add data will be used to increase the final output. How? The data collected is analyzed by AI on such variables as crop health and soil conditions, boosting final production, and it can also be used in harvesting, especially for crops that are difficult to gather.

AI is changing the workplace, and there are plenty of reasons to be optimistic. It is used to do lots of tedious and lengthy tasks, especially the low-skilled types of jobs that are labor-intensive. It means that employees will be retasked away from boring jobs and bring significant and positive change in the workplace.

For instance, artificial intelligence is used in the automotive industry to do repetitive tasks such as performing a routine operation in the assembly line, for example. Allowing a robot to care for well, robotic-tasks, has created a shift in the workforce.

Auto accidents are one of the most popular types of accidents that happen in America. It kills thousands of people annually. A whopping 95 percent of these accidents are caused byhuman error, meaning accidents are avoidable.

The number of accident cases will reduce as artificial intelligence is being introduced into the industry by the use of self-driving cars. On-going research in the auto industry is looking at ways AI can be used to improve traffic conditions.

Smart systems are currently in place in many cities that are used to analyze traffic lights at the intersections. Avoiding congestion leads to safer movements of vehicles, bicycles, and pedestrians.

Conclusion

Artificial intelligence is very useful in all industries as more research is being done to advance it. The advancements in this AI tech will be most useful if it is understood and trusted. An important part of it is that artificial intelligence and related technologies such as drones, robots, and autonomous vehicles can create around tens of millions of jobs over the next decade.

Having more jobs created not less will be great news for everyone. More jobs will help boost the GDP of the economy. Advancement in AI and its impressive computational power has already led to the concept of supercomputers and beyond.

Elena Randall is a Content Creator Who works for Top Software Companies, provides a top 10 list of top software development companies within the world. She is passionate about reading and writing.

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5 Reasons Why Artificial Intelligence Is Important To You