Computer scientists use TACC systems to generate synthetic objects for robot training.
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Using theoretical calculations, scientists showed that it would not be possible to control a superintelligent AI.
CSL's Systems and Networking Research Group (SyNRG) is defining a new sub-area of mobile technology that they call "earable computing."
Researchers have created a machine learning algorithm that can detect subtle signs of osteoarthritis on an MRI scan taken years before symptoms even begin.
Researchers explain how computer scientists and clinicians are trying to reduce fatal medical errors by building “ambient intelligence” into the spaces where patients reside.
Researchers develop new machine learning approach that shows promise in predicting Necrotizing enterocolitis; could lead to improved medical decision-making in neonatal ICUs.
Students at Cranfield University have designed computer models that can identify COVID-19 in X-rays.
Machine learning will drastically improve brain-computer interfaces and their ability to remain stabilized during use, greatly reducing or potentially eliminating the need to recalibrate these devices.
Experts have begun using artificial intelligence to create computer models that calculate the risk of a corona patient’s needing intensive care or a ventilator.
Researchers have developed a new approach to early diagnosis of lung cancer: a urine test that can detect the presence of proteins linked to the disease.
Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma.
Combining new wearable electronics and a deep learning algorithm could help disabled people wirelessly interact with a computer.
A smart shirt that measures lung function by sensing movements in the chest has proven to be accurate when compared to traditional testing equipment.
Researchers have developed a groundbreaking AI algorithm that can enable hearing aid users to take a more active part in conversations in noisy environments.
Using machine learning, a group of researchers demonstrated that it was possible to detect dementia from conversations in human-agent interaction.
Eric Schmidt has strong opinions about the healthcare system, its providers and professionals. He critized that the healthcare ecosystem was still being stuck in the “stone age" and challenges it to "focus on innovation".
Human-machine interaction is complex. Researchers investigate a new form of interaction between humans and machines.
BrainGate researchers demonstrated the first human use of a wireless transmitter capable of delivering high-bandwidth neural signals.
Researchers have created life forms that self-assemble a body from single cells and do not require muscle cells to move. They're faster, live longer, and can now record information.
Researchers have found that out of the more than 300 COVID-19 machine learning models are not suitable for detecting or diagnosing COVID-19 from standard medical imaging.
Researchers have developed system for smart speakers to monitor both regular and irregular heartbeats without physical contact.
The Fraunhofer Institutes project M³Infekt aims to develop a multi-modal, modular and mobile system of sensors for monitoring infectious diseases.
AI is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place.
A deep learning model that can predict how human genes and medicines will interact has identified at least 10 compounds that may hold promise as treatments for COVID-19.
A machine learning system learns on the job. By continuously adapting to new data inputs, this “liquid network” could aid decision-making in medical diagnosis.
Using mathematical image processing, scientists have found a way to create digital twins from human hearts.
Deep-learning methods have the potential to offer substantially better results, generating superior representations for characterizing the human brain.
Scientists have developed a machine learning method that crunches massive amounts of data to help determine which existing medications could improve outcomes in diseases for which they are not prescribed.
NIH BRAIN Initiative scientists used machine learning to redesign a bacterial ‘Venus flytrap’ protein that can monitor brain serotonin levels in real time.
Experts working at the intersection of robotics, machine learning, and physics-based simulation share how computer simulation could accelerate the development of "smart robots" which "might interact with humans"
Machine learning can be used to fill a significant gap in Canadian public health data related to ethnicity and Aboriginal status, according to research by a University of Alberta research epidemiologist.
Researchers have shown that they can measure those effects of the Corona pandemic on mental health by analyzing the language that people use to express their anxiety online.
An artificial intelligence-based detects early stages of Alzheimer’s through functional magnetic resonance imaging.
Researchers have created artificial intelligence algorithm that can automatically identify patients at high risk of intentional self-harm, based on the information in the clinical notes in the electronic health record.
A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers.
Researchers at the Hamlyn Centre, Imperial College London, have introduced a novel tool for generating accurate endoscopic datasets.
Researchers have developed a unique diagnostic tool that can detect dystonia from MRI scans, the first technology of its kind to provide an objective diagnosis of the disorder.
Scientists have developed a bioelectronic system driven by a machine learning algorithm that can shift the membrane voltage in living cells and maintain it at a set point for 10 hours.
AI is playing a key role in the Covid-19 response, but it could also be exacerbating inequalities within our health systems – a critical concern that is dragging the technology’s limitations back into the spotlight.
Researchers have shown that machine learning techniques helped an individual with paralysis learn to control a computer cursor using their brain activity.
The development of new medical technologies based on cutting-edge discoveries has accelerated during the coronavirus pandemic.
Scientists have paired 3D-printed, living human brain vasculature with advanced computational flow simulations to better understand tumor cell attachment to blood vessels.
Researchers have shown that federated learning is successful in the context of brain imaging, by being able to analyze MRI scans of brain tumor patients and distinguish healthy brain tissue from cancerous regions.
Researchers have developed robotic prosthetic legs which use motors that were originally designed for use on the robotic arm of the ISS.
Scientists have assembled a combination of data mining, machine-learning algorithms and compression-based analytics to bring the most useful data to the fore on an office computer.
Designed by a team at the NYU Tandon School of Engineering and an institute of the Max Planck Society, the four-legged, dog-sized, torque-controlled Solo 8 robot can easily be replicated by research labs around the world.
Researchers are collaborating with local partners to establish a network of portable, handheld ultrasound scanners that can soon accelerate COVID-19 diagnosis.
Pathologists who examined the computationally stained images could not tell them apart from traditionally stained slides.
Scientists are launching a project to apply machine learning methods to assess the role of climate variables in disease transmission
Using machine learning, a team of Western computer scientists and biologists have identified an underlying genomic signature for 29 different COVID-19 DNA sequences.
Researchers are developing a new high-precision radiology system for coronavirus pulmonary involvement.
A ‘pandemic drone’ to remotely monitor and detect people with infectious respiratory conditions is being developed.
“AI is the biggest technological breakthrough of our lifetime. It will boost the entire healthcare ecosystem and will eventually re-invent the way we deliver medicine entirely.”
Researchers have developed a computer model which predicts the neuronal activation patterns that the cochlear implant creates in the auditory nerve fibers.
Thanks to smart software doctors will soon be able to detect early signs of esophageal cancer in patients with so-called Barrett’s esophagus.
An AI platform can analyze genomic data extremely quickly, picking out key patterns to classify different types of colorectal tumors and improve the drug discovery process.
Using machine learning, a prototype microscope teaches itself the best illumination settings for diagnosing malaria.
Ensembles created using models submitted to the RSNA Pediatric Bone Age Machine Learning Challenge convincingly outperformed single-model prediction of bone age.
Dementia screening could be as easy as using a smartphone app that listens to elderly people speak.
Researchers show that deep learning algorithms perform similar to human experts when classifying blood samples from patients suffering from acute myeloid leukemia.
Researchers have been investigating whether artificial intelligence might be used to steer a catheter automatically and reliably to a blocked blood vessel.
An algorithm did better than experts radiologists at finding tiny brain hemorrhages in head scans — an advance that one day may help doctors treat patients with strokes.
Based on a convolutional neural network the tool is able to provide results within seconds, thus supporting the doctor with comprehensive image analysis.
A 4-limb robotic system controlled by brain signals helped a tetraplegic man to move his arms and walk using a ceiling-mounted harness for balance.
Sensitive synthetic skin enables robots to sense their own bodies and surroundings – a crucial capability if they are to be in close contact with people.
Researchers have developed a new smart speaker skill that lets a device use white noise to monitor sleeping babies breathing and movement.
A research team has succeeded in identifying specific patterns in Electro-Encephalogram (EEG) analyses that the deep learning network uses for making prognosis decisions.
Scientists have successfully tested neuroprosthetic technology that combines robotic control with users’ voluntary control, opening avenues in the new interdisciplinary field of shared control for neuroprosthetic technologies.
Researchers have developed a technology to help clinicians "see" and map patient pain in real-time, through special augmented reality glasses.
Researchers at the University of Washington have developed a new tool to monitor people for cardiac arrest while they’re asleep without touching them.
A machine learning method discovered a clue in people’s language predictive of the emergence of psychosis — the frequent use of words associated with sound.
The Open-Source Bionic Leg will enable investigators to efficiently solve challenges associated with controlling bionic legs across a range of activities in the lab and out in the community.
Researchers have demonstrated that their technique can stop the catheter at the right target and identify the source type with a 95.25 percent success rate.
Researchers have created a new app that can detect fluid behind the eardrum by simply using a piece of paper and a smartphone’s microphone and speaker.
A state-of-the-art brain-machine interface created by UC San Francisco neuroscientists can generate natural-sounding synthetic speech by using brain activity to control a virtual vocal tract – an anatomically detailed computer simulation including the lips, jaw, tongue and larynx.
Researchers have developed a new design method that shows promise in enabling the efficient design and fabrication of soft robots using a 3D printer.
Researchers have created new AI software that can identify cardiac rhythm devices in x-rays more accurately and quickly than current methods.
A video recording of an infant lying in bed can be analyzed with artificial intelligence to extract quantitative information useful for assessing the child’s development as well as the efficacy of ongoing therapy.
Researchers have built a set of magnetic ‘tweezers’ that can position a nano-scale bead inside a human cell in three dimensions with unprecedented precision.
Researchers are working on a smartphone app that could help diagnose autism in minutes – and provide ongoing therapy as well, all with fewer visits to specialized clinics.
Patients could soon get faster and more accurate diagnoses with new software that can automatically detect signs of diabetes, heart disease and cancer from medical images.
A machine learning algorithm was able to sort children with arthritis into distinct categories based on their patterns of inflamed joints in the body in a way that was also predictive of disease outcome.
A team of experts led by two University of Michigan researchers calls for attention to this shadow record.
Scientists have developed a soft wearable hand robot that can aid the hand-disabled by using machine learning algorithm and sensory hardware.
Researchers have developed an app that uses sonar to monitor someone's breathing rate and sense when an opioid overdose has occurred.
Doctors could get a head start treating cancer thanks to new AI developed at the University of Surrey that is able to predict symptoms and their severity throughout the course of a patient’s treatment.
Researchers have developed a system using artificial intelligence to quickly diagnose and classify brain hemorrhages and to provide the basis of its decisions from relatively small image datasets.
UCLA-led team produces images on a laptop that match the quality of those from high-end equipment.
SubtlePET’s AI-powered technology allows hospitals and imaging centers to enhance images from faster scans leading to an improved patient experience during imaging procedures.
Medical software that overlays tumour information from MRI scans onto ultrasound images can help guide surgeons conducting biopsies and improve prostate cancer detection.
In a matter of seconds, a new algorithm read chest X-rays for 14 pathologies, performing as well as radiologists in most cases, a Stanford-led study says.
Researchers are working on an interactive robot called Pharos that will help the elderly with their daily household chores.
An engineer is leading a team of researchers, health care providers and industry to fast-track the commercialization of a groundbreaking robotic rehabilitation system.
Scientists have developed machine learning algorithms that can predict yeast metabolism from its protein content.
Researchers use augmented reality tools to connect health care professionals in war zones, natural disasters and in rural areas with more experienced surgeons and physicians around the world.
A team at the University of Auckland's Bioengineering Institute has created a virtual 3D heart that could have a major impact on treatment of the most common heart rhythm disturbance, atrial fibrillation (AF).
Scientists have used machine learning to improve the performance of prosthetic hands. The researchers said the findings, could spark a "new generation of prosthetic limbs.
Researcher have developed algorithms that analyze patients‘ imaging data and calculate surgical risks. This makes liver cancer surgery safer and easier to plan.