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Using electric signals from human brains, new software can perform computerized image editing

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Soon, computers could sense that users have a problem and come to the rescue. This is one of the possible implications of new research at University of Copenhagen and University of Helsinki. "We can make a computer edit images entirely based on thoughts generated by human subjects. The computer has absolutely no prior information about which features it is supposed to edit or how. Nobody has ever done this before," says Associate Professor Tuukka Ruotsalo, Department of Computer Science, University of Copenhagen.


AI Tool Lets Users Edit Images With Their Thoughts

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Soon, we won't need to use the Help function. The computer will sense that we have a problem and come to the rescue by itself. This is one of the possible implications of new research at University of Copenhagen and University of Helsinki. "We can make a computer edit images entirely based on thoughts generated by human subjects. The computer has absolutely no prior information about which features it is supposed to edit or how. Nobody has ever done this before," says Associate Professor Tuukka Ruotsalo, Department of Computer Science, University of Copenhagen.


Let your mind control the computer

#artificialintelligence

Soon, we won't need to use the Help function. The computer will sense that we have a problem and come to the rescue by itself. This is one of the possible implications of new research at University of Copenhagen and University of Helsinki. "We can make a computer edit images entirely based on thoughts generated by human subjects. The computer has absolutely no prior information about which features it is supposed to edit or how. Nobody has ever done this before," says Associate Professor Tuukka Ruotsalo, Department of Computer Science, University of Copenhagen.


Bridging the knowledge gap on AI and machine-learning technologies – Physics World

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How much is too much? These are questions that cut to the heart of a complex issue currently preoccupying senior medical physicists when it comes to the training and continuing professional development (CPD) of the radiotherapy physics workforce. What's exercising management and educators specifically is the extent to which the core expertise and domain knowledge of radiotherapy physicists should evolve to reflect – and, in so doing, best support – the relentless progress of artificial intelligence (AI) and machine-learning technologies within the radiation oncology workflow. In an effort to bring a degree of clarity and consensus to the collective conversation, the ESTRO 2022 Annual Congress in Copenhagen last month featured a dedicated workshop session entitled "Every radiotherapy physicist should know about AI/machine learning…but how much?" With several hundred delegates packed into Room D5 at the Bella Center, speakers were tasked by the session moderators with defending a range of "optimum scenarios" to align the know-how of medical physicists versus emerging AI/machine-learning opportunities in the radiotherapy clinic.


Machine Learning Tool Advances Research on Rheumatoid and Osteoarthritis

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A team led by investigators at the Hospital for Special Surgery (HSS) in New York City reports that their computer vision tool effectively distinguishes rheumatoid arthritis (RA) from osteoarthritis (OA) in joint tissue taken from patients who underwent total knee replacement (TKR). The results suggest the machine learning model will help improve research processes in the short term and optimize patient care in the future, according to the researchers who presented their findings at the European Alliance of Associations for Rheumatology (EULAR) Congress 2022 in Copenhagen, Denmark. TKR is often the only management option for patients with severe knee joint damage, the scientists said, who added that identifying which disease caused the joint damage is essential for guiding treatment plans, given that RA is a systemic, inflammatory disease that may also affect the eyes or lining around the heart, while OA affects just the joints. "We know there are many more immune cells present in the synovium, or joint tissue, of patients with RA compared to those with OA," said Bella Mehta, MBBS, rheumatologist at HSS. "But precisely how many more has not been clear." "Pathologists typically assess images of synovium to determine the extent of inflammation using a combination of approaches, including assigning the level of immune cell infiltration on a scale from 0 to 4," noted Dana Orange, MD, rheumatologist at HSS, and assistant professor at Rockefeller University.


PharmiWeb.com: The Heart Of Life Sciences On The Web - AI Summary

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PrecisionLife today announces that it has acquired its long-term Danish technology development partner GenoKey ApS, bringing together the leaders in combinatorial analytics and large-scale genomic analysis, and enabling PrecisionLife to continue its expansion as an AI-enabled precision medicine company. PrecisionLife's platform, which includes technology developed with GenoKey, enables the company to gain unique insights into genes associated with disease, as biomarkers and as targets for drug discovery. In addition to its expertise and IP, PrecisionLife will benefit from GenoKey's strong relationships with the Danish health system and leading academic clinical research centers including Aalborg, Aarhus and Copenhagen. Recently, PrecisionLife joined the pan-European FEMaLe consortium led by researchers from Aarhus University, which is a €5.3M international EU Horizon 2020 project that aims to develop precision medicine approaches to improve the diagnosis, treatment and quality of life of patients with endometriosis. PrecisionLife will maintain its core platform development operations at GenoKey's site in Denmark with further team expansion in the region planned.


AI Can Use Infrared Signature to Sort Plastics - ASME

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No matter how conscientious the consumer, by the time the material gets to the end of the conveyor belt at the recycling plant, most plastics end up mixed together. Due to the rather rudimentary sorting techniques in use, only a small percentage of the plastic we try to recycle ends up getting recycled. "The ordinary consumer, with the best intentions--and also the correct procedure--puts everything in the plastic bin. We get it all," said Mogens Hinge, an associate professor in the department of biological and chemical engineering and process and materials engineering at Denmark's Aarhus University, and co-author of the paper "Plastic classification via in-line hyperspectral camera analysis and unsupervised machine learning," which appeared in Vibrational Spectroscopy this year. "Now we have a problem: we can wash it, but we can't unmix it. And plastic is not just plastic."


Horses and pigs can distinguish between negative and positive sounds in human speech

Daily Mail - Science & tech

From'Babe' to'Black Beauty', popular culture is constantly telling us that speaking to animals gently and'politely' is the best way to get them to do our bidding. Now a new study has shown the same is true in the real world, as domesticated animals like pigs and horses can tell the difference between negative and positive sounds in human speech. Researchers from the University of Copenhagen's Department of Biology and ETH Zurich found that the animals reacted react more strongly to'negatively charged' human voices. In some cases they even seemed to mirror the emotion expressed in the human voice, according to the researchers. 'That'll do, pig': The findings in the study backs up teachings in films like'Babe' where characters speak politely to their furry companions The stallion in'Black Beauty' goes through many good and bad owners, and researchers have found that this experience could have bearing on the wellbeing of real-life horses Researchers concluded that it is most likely that horses may be able to perceive and interpret each other's sounds by virtue of their common biology.


How robots can help build offshore wind turbines more quickly

The Japan Times

The invasion of Ukraine has put the U.S. and Europe on a wartime mission to abandon Russian fossil fuels. This series looks at speeding up zero-carbon alternatives by lowering political and financial barriers. Sign up here to get the next story sent to your inbox. Trying to attach a million-dollar, 60-ton wind turbine blade to its base is challenging in any circumstance -- getting the angle wrong by even a fraction of a degree could affect the machine's ability to generate power. Now imagine trying to do it in the middle of the North Sea, one of the world's windiest spots, with waves swelling around you. It's like tying a thread to a kite at the beach and then trying to put it through the eye of a needle.


New machine learning maps the potentials of proteins

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The biotech industry is constantly searching for the perfect mutation, where properties from different proteins are synthetically combined to achieve a desired effect. It may be necessary to develop new medicaments or enzymes that prolong the shelf-life of yogurt, break down plastics in the wild, or make washing powder effective at low water temperature. New research from DTU Compute and the Department of Computer Science at the University of Copenhagen (DIKU) can in the long term help the industry to accelerate the process. In the journal Nature Communications, the researchers explain how a new way of using Machine Learning (ML) draws a map of proteins, which makes it possible to appoint a candidate list of the proteins that you need to examine more closely. In recent years, we have started to use Machine Learning to form a picture of permitted mutations in proteins.