Tag Archives: AI

Machine Learning Predicts Heart Failure

Every year, roughly one out of eight U.S. deaths is caused at least in part by heart failure. One of acute heart failure’s most common warning signs is excess fluid in the lungs, a condition known as “pulmonary edema.” A patient’s exact level of excess fluid often dictates the doctor’s course of action, but making such determinations is difficult and requires clinicians to rely on subtle features in X-rays that sometimes lead to inconsistent diagnoses and treatment plans.

To better handle that kind of nuance, a group led by researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) has developed a machine learning model that can look at an X-ray to quantify how severe the edema is, on a four-level scale ranging from 0 (healthy) to 3 (very, very bad). The system determined the right level more than half of the time, and correctly diagnosed level 3 cases 90 percent of the time.

Working with Beth Israel Deaconess Medical Center (BIDMC) and Philips, the team plans to integrate the model into BIDMC’s emergency-room workflow this fall.

This project is meant to augment doctors workflow by providing additional information that can be used to inform their diagnoses as well as enable retrospective analyses,” says PhD student Ruizhi Liao, who was the co-lead author of a related paper with fellow PhD student Geeticka Chauhan and MIT professors Polina Golland and Peter Szolovits.

The team says that better edema diagnosis would help doctors manage not only acute heart issues, but other conditions like sepsis and kidney failure that are strongly associated with edema.

As part of a separate journal article, Liao and colleagues also took an existing public dataset of X-ray images and developed new annotations of severity labels that were agreed upon by a team of four radiologists. Liao’s hope is that these consensus labels can serve as a universal standard to benchmark future machine learning development.

An important aspect of the system is that it was trained not just on more than 300,000 X-ray images, but also on the corresponding text of reports about the X-rays that were written by radiologists. “By learning the association between images and their corresponding reports, the method has the potential for a new way of automatic report generation from the detection of image-driven findings,says Tanveer Syeda-Mahmood, a researcher not involved in the project who serves as chief scientist for IBM’s Medical Sieve Radiology Grand Challenge. “Of course, further experiments would have to be done for this to be broadly applicable to other findings and their fine-grained descriptors.”

Chauhan, Golland, Liao and Szolovits co-wrote the paper with MIT Assistant Professor Jacob Andreas, Professor William Wells of Brigham and Women’s Hospital, Xin Wang of Philips, and Seth Berkowitz and Steven Horng of BIDMC.

Source: https://news.mit.edu/

China: Explosive Growth In The Digital Economy

China has over 110 million 5G users and is expected to have more than 600,000 5G base stations by the end of this year, covering all cities at prefecture level and above, according to the 5G Innovation and Development Forum held on Sept 15 during the Smart China Expo Online in southwest China’s Chongqing municipality.

Since 5G licenses for commercial use for more than one year were issued, the country has made steady progress in the construction of its 5G network infrastructure, said Han Xia, director of the telecom department at the Ministry of Industry and Information Technology, adding that Chinese telecommunications companies have already built over 500,000 5G base stations with over 100 million 5G internet terminals.

So far, 5G has been deployed in sectors and fields including ports, machinery, automobiles, steel, mining and energy, while 5G application has been accelerated in key areas such as industrial internet, Internet of Vehicles, medical care, and education, Han noted.

The value of the country’s industrial internet hit 2.13 trillion yuan last year, Yin Hao, an academician from the Chinese Academy of Sciences said at the forum, adding that the figure is expected to exceed 5 trillion yuan in 2025.

The integrated development of “5G plus industrial internet” can create new products, generate new models and new forms of business, reduce enterprises’ operating costs, improve their production efficiency, and optimize their resource allocation, Yin noted.

According to Chen Shanzhi, vice president of the China Information and Communication Technologies Group Corporation (CICT), the combination of 5G and other emerging information technologies, including artificial intelligence, cloud computing and big data, will help accelerate the integrated development and innovation of other sectors and bring about explosive growth in the digital economy.

http://global.chinadaily.com.cn/

Elon Musk Promises Demo Of A Working Neuralink Device Today

Neuralink, the secretive firm has been relatively quiet since its first public event in July 2019, when Musk and his team explained how the firm plans to use chips to link human brains up to computers. On Tuesday, Musk revealed more details about the event via his Twitter page. The event is set to feature a “live webcast of a working Neuralink device,” giving the public its first glimpse of the device in action. The stream is scheduled to take place on FRIDAY, AUGUST 28 AT 3 P.M. PACIFIC TIME, or 12 p.m. Eastern time.

The motto hints at one of Musk’s biggest goals with Neuralink. While it’s currently focused on creating chips that could help medical patients, Musk has spoken before about his fear that artificial intelligence could one day outsmart humanity. Neuralink, Musk reasons, could help humans more effectively communicate with these smarter systems, and develop a symbiotic relationship with machines.

It’s important that Neuralink solves this problem sooner rather than later, because the point at which we have digital superintelligence, that’s when we pass the singularity and things become just very uncertain,” Musk said in a November 2019 interview.

It’s an ambitious goal, but Musk has hinted that Friday’s event will be a more grounded affair. That doesn’t mean there won’t be surprises in store, however, and Musk’s comments suggest it could offer something spectacular.

Source: https://www.inverse.com/

AI Fighter Jet Obliterates Human Air Force Pilot

The never-ending saga of machines outperforming humans has a new chapter. An AI algorithm has again beaten a human fighter pilot in a virtual dogfight. The contest was the finale of the U.S. military’s AlphaDogfight challenge, an effort to “demonstrate the feasibility of developing effective, intelligent autonomous agents capable of defeating adversary aircraft in a dogfight.

Last August, Defense Advanced Research Project Agency, or DARPA,  selected eight teams ranging from large, traditional defense contractors like Lockheed Martin to small groups like Heron Systems to compete in a series of trials in November and January. In the final, on Thursday, Heron Systems emerged as the victor against the seven other teams after two days of old school dogfights, going after each other using nose-aimed guns only. Heron then faced off against a human fighter pilot sitting in a simulator and wearing a virtual reality helmet, and won five rounds to zero.

The other winner in Thursday’s event was deep reinforcement learning,wherein artificial intelligence algorithms get to try out a task in a virtual environment over and over again, sometimes very quickly, until they develop something like understanding. Deep reinforcement played a key role in Heron System’s agent, as well as Lockheed Martin’s, the runner up.

https://www.defenseone.com/

The U.S. Wastes $161B Worth Of Food Every Year. A.I. Is Helping Us Fix That

When you see pictures of food waste, it just blows you away,” said Stefan Kalb, a former food wholesaler. “I mean, shopping cart after shopping cart of food waste. What happens with the merchandisers when they walk through the store, and they’re pulling products that have expired, is that they’ll put it in a shopping cart and just roll it to the back. It’s almost one of those dystopian [movie] pictures … cartons of milk just piled up in a grocery cart. The ones that didn’t make it.”

In the United States, somewhere between 30% and 40% of the food that’s produced is wasted. That’s the equivalent of $161 billion every single year. The U.S. throws away twice as much food as any other developed country in the world. There are all sorts of reasons this is a problem but A.I. could could solve it.

Kalb’s company is one of several startups — let’s call them the “Internet of Groceries” — using some impressively smart machine learning tools to help with this significant problem. Kalb is the co-founder of Shelf Engine, a company that uses analytics to help retailers better examine the historical order and sales data on their products so as to make better decisions about what to order. This means reduced waste and bigger margins. The company also buys back unsold stock, thereby guaranteeing the sale for a retailer.

We haven’t previously automated this micro-decision that is happening at the grocery store with the buyer,” said Kalb . “The buyer of the store is predicting how much to order — and of what. It’s a very hard decision, and they’re doing it for hundreds and thousands of items. You have these category buyers that just walk through the store to decide how they’re gonna change their bread order or their produce order or their milk order. They’re making these micro-decisions, and it’s costing them tremendous money. If we can automate that part, then we can really make a large impact in the world.”

Source: https://www.digitaltrends.com/

The Human Vs. Drone Dogfight

The U.S. Air Force will square off an AI-powered drone against a fighter jet flown by a real, live human being. The service wants to know if AI powered by machine learning can beat a human pilot with actual cockpit experience. The result will help the Air Force determine if AI-powered fighters are a viable alternative to human-powered fighters, the results of which could have far-reaching consequences for aerial warfare.

Air Force Magazine reports Lt. Gen. Jack Shanahan, head of the Pentagon’s Joint Artificial Intelligence Center, stated that the fly off would take place in 2021. Shanahan was speaking at a virtual event of the Mitchell Institute for Aerospace Studies.

Earlier reports stated that the fly-off would likely involve an older plane such as the F-16 before progressing to more advanced jets like the F-35 and F-22. If that’s the case, the Air Force will probably fly an unmanned F-16 versus a manned F-16, to make sure the human pilot and AI have as level a playing field as possible. The Air Force has already developed a remote flying mechanism, converting the F-16 to QF-16 target drones , and presumably the AI would control that mechanism.

The Pentagon has flown fighters against drones before. In 1971, spy drone manufacturer Teledyne Ryan modified their BFM-34 reconnaissance drone with the Maneuverability Augmentation System for Tactical Air Combat Simulation, or MASTACS. The result was the BFM-34E unmanned fighter jet. Fast, maneuverable, and with a low radar cross section, the BFM-34E was a difficult opponent for a human fighter pilot to fly against. A paper prepared for the U.S. Air Force’s Air University described the drone:Both the USAF and USN used this UAV to train their best pilots in simulated air combat. At Tyndall Air Force Base in Florida, the BGM-34F was used as a target in the annual William Tell air combat competition. This UAV routinely outmaneuvered manned F-15 and F-16 aircraft; one named ‘Old Red’ survived eighty-two dogfights. The USN used the MASTACS as a “graduation exercise” at their Top Gun Weapons School.

Despite the BGM-34F’s unexpected success the Navy and Air Force had no interest in an unmanned fighter, and the program was never pursued.

Source: https://www.popularmechanics.com/

Covid Voice Detector

Record your voice to help save lives!

Carnegie Mellon University, voca.ai, telling.ai, hat-ai.com and Incremental Healthcare LLC collaboratively bring you this experimental system designed to detect signatures of Covid-19 infections in your voice. This is a free service.​

The team of voice scientists and engineers are working on voice forensic technologies. The Covid-19 pandemic is spreading rapidly across the world. There is a growing shortage of medical testing facilities. Tens of thousands of potentially infected people who need to be tested do not have easy access to medical tests. The goal is to develop a voice-based testing system for Covid-19, that could potentially reach every person in the world.​

A website provides Covid-19 assessment from voice. You may try it out, but please see the disclaimer. To make this system accurate, the research team urgently need examples of voices from healthy and infected people. Please use this system to donate your voice. Please ask your friends family to also do so. Together we may help save lives.​

What this system currently provides: This is an AI-powered system that analyzes your voice and gives you a score. The score is a rating on a scale of 1-10 that tells you the likelihood that your voice carries signatures of Covid-19. The higher the returned rating, the greater the likelihood that you may be infected. In addition, the system provides an assessment of your lung capacity where possible. ​

Please remember that this system is still very much under development. It will improve as the scientists obtain more data from healthy and infected individuals. Everyone is urged to contribute data, particularly if you are or have been infected. Please act responsibly and provide accurate information. The accuracy of the data we obtain will dictate our ability to succeed.

Source; https://cvd.lti.cmu.edu/

Commercial Nuclear Fusion Is Closer Than Ever

Nuclear fusion has been seen as the unattainable holy grail of clean energy for decades, but just in the last year it’s been seeming more and more within reach. As catastrophic climate change looms just over the horizon, the scientific community has galvanized to find more and better solutions to decarbonizing the global economy and replacing fossil fuels with a commercially viable, renewable, and green alternative. While much of the time and capital investment has flowed to more realistic options like solar and wind, some researchers have been dedicating their time and energy to capturing the energy of the sun here on earth–a silver bullet solution to global warming.

Conventional nuclear energy has also been hailed as a good, greenhouse gas emissions-free alternative to fossil fuels, but it has some major drawbacks, from the rare but catastrophic instance of nuclear meltdown to the industrial byproduct of nuclear waste. Nuclear fission, which is what nuclear energy plants currently use to create massive amounts of energy by splitting atoms, creates radioactive waste that remains hazardous for tens of thousands of years, if not longer.

The beauty of nuclear fusion is that, not only does it produce energy without creating radioactive waste since it can be achieved using only hydrogen or lithium, it’s also several times more powerful than fission. If we were ever able to harness it in a commercially viable way, it would mean the end of the oil-based economy as we know it. That’s why any news about nuclear fusion is major news. And in the past couple of years, there’s been a lot of new reports emerging about commercial nuclear fusion getting closer and closer to becoming a reality.

Last summer, reps from the International Thermonuclear Experimental Reactor (ITER), an intergovernmental project headquartered in the south of France, reported that they are a mere six and a half years away from achieving first plasma inside their tokamak–in other words: nuclear fusion by just 2025. Then, just a month later in August, 2019, Oak Ridge National Laboratory reported their own nuclear fusion breakthrough, which uses novel implementation of AI and supercomputing to successfully scale up nuclear fusion experiments and manage plasma.

Then, in October, the Los Alamos National Laboratory‘s Plasma Liner Experiment (PLX) unveiled a totally new approach to nuclear fusion, using the very science-fiction combination of plasma guns, magnets, and lasers. According to the American Physical Society, “the PLX machine combines aspects of both magnetic confinement fusion schemes (e.g. tokamaks) and inertial confinement machines like the National Ignition Facility (NIF). The hybrid approach, although less technologically mature than pure magnetic or inertial confinement concepts, may offer a cheaper and less complex fusion reactor development path.” That project is projected to be up and running by the end of this year.

And now, just this week, there are new and exciting claims about yet another novel fusion technology to vie for the best path toward commercial nuclear fusion. Startup HB11, which has its impetus at Australia’s University of New South Wales (UNSW), has pioneered a technology that uses lasers to encourage nuclear fusion between hydrogen and boron without the use of radioactive materials to facilitate the reaction. They’re so confident about the technology that they have already applied for and received patents in the United States, Japan, and China.

The secret,” reports Popular Mechanics, “is a cutting-edge laser and, well, an element of luck.” According to managing director Warren McKenzie, as quoted by New Atlas,You could say we’re using the hydrogen as a dart, and hoping to hit a boron, and if we hit one, we can start a fusion reaction.” While this may sound a little wishy-washy, McKenzie says that the approach is actually more precise than using extreme heat to facilitate fusion because the laser is directed, whereas heat-based reactors waste huge amounts of energy heating up the entire reactor and waiting for a collision to take place.

This means that this new technology–which is now four decades in the making–could make machines like the tokamak obsolete. UNSW emeritus professor Heinrich Hora’s design “seeks to not just compete with but replace entirely the extremely high-temperature current technologies to achieve fusion. These include fussy and volatile designs like the tokamak or stellarator, which can take months to get up to functionality and still spin out of working order in a matter of microseconds.”

Last but not least, two months ago, Newsweek reported that China is about to start operation on its “artificial sun“—a nuclear fusion device that produces energy by replicating the reactions that take place at the center of the sun. If successful, the device could edge scientists closer to achieving the ultimate goal of nuclear fusion: near limitless, cheap clean energy.

Source: https://www.newsweek.com/
AND
https://oilprice.com/

AI Detects Visual Signs Of Covid-19

Zhongnan Hospital of Wuhan University in Wuhan, China, is at the heart of the outbreak of Covid-19, the disease caused by the new coronavirus SARS-CoV-2 that has shut down cities in China, South Korea, Iran, and Italy. That’s forced the hospital to become a testbed for how quickly a modern medical center can adapt to a new infectious disease epidemic.

One experiment is underway in Zhongnan’s radiology department, where staff are using artificial intelligence software to detect visual signs of the pneumonia associated with Covid-19 on lung CT scan images. Haibo Xu, professor and chair of radiology at Zhongnan Hospital, says the software helps overworked staff screen patients and prioritize those most likely to have Covid-19 for further examination and testing 

Detecting pneumonia on a scan doesn’t alone confirm a person has the disease, but Xu says doing so helps staff diagnose, isolate, and treat patients more quickly. The software “can identify typical signs or partial signs of Covid-19 pneumonia,” he wrotel. Doctors can then follow up with other examinations and lab tests to confirm a diagnosis of the disease. Xu says his department was quickly overwhelmed as the virus spread through Wuhan in January.

The software in use at Zhongnan was created by Beijing startup Infervision, which says  its Covid-19 tool has been deployed at 34 hospitals in China and used to review more than 32,000 cases. The startup, founded in 2015 with funding from investors including early Google backer Sequoia Capital, is an example of how China has embraced applying artificial intelligence to medicine.

China’s government has urged development of AI tools for healthcare as part of sweeping national investments in artificial intelligence. China’s relatively lax rules on privacy allow companies such as Infervision to gather medical data to train machine learning algorithms in tasks like reading scans more easily than US or European rivals.

Infervision created its main product, software that flags possible lung problems on CT scans, using hundreds of thousands of lung images collected from major Chinese hospitals. The software is in use at hospitals in China, and being evaluated by clinics in Europe, and the US, primarily to detect potentially cancerous lung nodulesInfervision began work on its Covid-19 detector early in the outbreak after noticing a sudden shift in how existing customers were using its lung-scan-reading software. In mid-January, not long after the US Centers for Disease Control advised against travel to Wuhan due to the new disease, hospitals in Hubei Province began employing a previously little-used feature of Infervision’s software that looks for evidence of pneumonia, says CEO Kuan Chen. “We realized it was coming from the outbreak,” he says.

Source: https://www.wired.com/

Nanoscale Device Acts Like The Brain’s Visual Cortex To Directly See Things

In a new study published in February 2020 in the journal Science Advances, researchers report the development of a nanoscale device that acts like the brain’s visual cortex to directly see things in its path. The scientists created a new superstructure through the use of two nanomaterials in tandem that could help to make a machine that uses AI to simulate a human mind‘s function.

This is a baby step toward developing neuromorphic computers, that can simultaneously process and memorize information. At some time in the future, this invention may help to make robots that can think like humans,” researcher Jayan Thomas says,  The big advantage of the current approach is in its saving of energy for processing as well as the time required for computation.

 

Another researcher, Tania Roy, predicted that the new technology might be applied to drones that can fly unaided to remote locations to find people in various dangerous situations. The problem with current drones is, she says, because “These drones need connectivity to remote servers to identify what they scan with their camera eye. Our device makes this drone truly autonomous because it can see just like a human.

With earlier research, scientists succeeded in making a camera that can create an image of what is observed, and then upload it for processing and image recognition to a server. The current device, she says, not only sees the image but also instantly recognizes it.

According to the researchers, this could also be extremely valuable for defense applications, such as helping soldiers see better on a battlefield. Another potential advantage is that, according to the co-first author Sonali Das, “Our device can sense, detect and reconstruct an image along with extremely low power consumption, which makes it capable for long-term deployment in field applications.”

The scientists tested out the device in face recognition experiments. These were only meant to be tests to check out how well the neuromorphic computing helped the machine to see objects. Describing these as preliminary, Thomas says they wanted to assess the optoelectronic device. “Since our device mimics vision-related brain cells, facial recognition is one of the most important tests for our neuromorphic building block.”

Source: https://www.news-medical.net/