Researchers have built an intelligent mobile robot scientist that can work 24-7, carrying out experiments by itself.
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Researchers are using generative adversarial networks to improve brain-computer interfaces for people with disabilities.
Researchers are developing new techniques for improving 3D displays for virtual and augmented reality technologies.
Purdue University engineers and physIQ have developed a viral detection algorithm for smartwatches.
Scientists have developed an algorithm for rapid, computerized diagnosis of COVID-19, overcoming the limitations of reverse transcription polymerase chain reaction.
An AI-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy.
A lightweight powered exoskeleton helps lower-limb amputees walk with much less effort.
Data privacy and security concerns hamper large-scale studies. Researchers have developed a potential solution.
The use of blockchain technology as a communication tool for a team of robots could provide security and safeguard against deception.
Secure AI Labs is expanding access to encrypted health care data to advance AI-driven innovation in the field.
AI-based solution FAITH is designed to monitor the mental health status of people who have undergone cancer treatment.
More than 20 hospitals from across the world together with NVIDIA have used AI to predict Covid patients’ oxygen needs on a global scale.
Researchers have developed a method to integrate sensing capabilities into 3D printable structures comprised of repetitive cells.
An electronic “nose” is capable of detecting with 86% accuracy when a lung transplant is beginning to fail.
Researchers have developed a technology to help clinicians "see" and map patient pain in real-time, through special augmented reality glasses.
Researchers have used machine learning to help reconstruct three-dimensional micro-CT images of fibrous materials.
Researchers have inserted small magnetic beads into muscle tissue within an amputated residuum for more precise control of prosthetic limbs.
Researchers have produced a low-cost device to detect SARS-CoV-2 with biosensors.
Tests show that the device can help patients safely and effectively manage their blood glucose levels and reduce the risk of low blood sugar levels.
Machine learning can accurately predict cardiovascular disease and guide treatment — but models that incorporate social determinants of health better capture risk and outcomes for diverse groups.
This overview introduces smart insulin delivery systems and more innovations that help patients and doctors guide decision-making in diabetes care.
AI tools models are a powerful tool in cancer treatment. However, unless these algorithms are properly calibrated, they can sometimes make inaccurate or biased predictions.
A wearable computer vision device can reduce collisions for both people who are blind or those who are visually impaired and using a long cane and/or guide dog by 37 percent, compared to using other mobility aids alone.
A wearable brain-machine interface system could improve the quality of life for people with motor dysfunction or paralysis, even those struggling with locked-in syndrome.
Scientists have developed an algorithm to help a robot find efficient motion plans to ensure physical safety of its human counterpart.
Every day, elderly people fall – be it at home or in care facilities. Lindera aims to reduce the risk of falling with the help of artificial intelligence.
Machine learning has the potential to vastly advance medical imaging, particularly CT scanning, by reducing radiation exposure and improving image quality.
Researchers aim to speed up developing drugs against brain diseases through cutting-edge technology. They are generating an innovative technology platform based on high-density microelectrode arrays and 3D networks of human neurons.
Researchers have discovered how to tailor-make artificial body parts and other medical devices with built-in functionality that offers better shape and durability, while cutting the risk of bacterial infection at the same time.
Researchers used an artificial intelligence (AI) algorithm to sift through terabytes of gene expression data to look for shared patterns in patients with past pandemic viral infections, including SARS, MERS and swine flu.
A team of engineers from Rensselaer Polytechnic Institute and clinicians from Massachusetts General Hospital developed a deep learning algorithm that can help assess a patient's risk of cardiovascular disease with the same low-dose computerized tomography (CT) scan used to screen for lung cancer.
To help patients manage their mental wellness between appointments, researchers at Texas A&M University have developed a smart device-based electronic platform that can continuously monitor the state of hyperarousal, one of the signs of psychiatric distress.
The University of Texas at San Antonio has established a wearables and AI laboratory to provide precision treatment plans to improve learning among those diagnosed with autism spectrum disorder (ASD).
A new study from the Mayo Clinic found that differences between a person's age in years and his or her biological age, as predicted by an artificial intelligence (AI)-enabled EKG, can provide measurable insights into health and longevity.
Researchers are developing a smart wrist-worn device for monitoring of atrial fibrillation – a condition, which if left untreated can lead to serious health complications and even death.
Scientists in Dresden are expanding their digital health expertise in multiple sclerosis (MS) therapy and research with an ambitious scientific project - creating a "digital twin“ from data.
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.
Scientists have used an implanted sensor to record the brain signals associated with handwriting, and used those signals to create text on a computer in real time.
Researchers have shown that a group of small autonomous, self-learning robots can adapt easily to changing circumstances. They connected the simple robots in a line, after which each individual robot taught itself to move forward as quickly as possible.
AI-driven healthcare has the potential to transform medical decision-making and treatment, but these algorithms must be thoroughly tested and continuously monitored to avoid unintended consequences to patients.
Scientists have developed a more accurate navigation system that allows robots to better negotiate busy clinical environments in general and emergency departments more specifically.
Medtronic partners with Surgical Theater to provide the first augmented reality platform for use in real-rime during complex cranial procedures.
Using AI, researchers have succeeded in making the mass analysis of proteins from any organism significantly faster than before and almost error-free.
The combination of a 2Photon 3D-printer with an innovative hydrogel-based bioink allows the direct printing of 3D structures containing living cells at both the meso- and microscale.
Artificial intelligence could help to optimise the development of antibody drugs. This leads to active substances with improved properties, also with regard to tolerability in the body.
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.
Deep learning-based system enables dermatologist-level identification of suspicious skin lesions from smartphone photos, allowing better screening.
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.
Successful precision cancer diagnosis through an AI analysis of multiple factors of prostate cancer. Potential application of the precise diagnoses of other cancers by utilizing a urine test.
Using mathematical image processing, scientists have found a way to create digital twins from human hearts.
Computer scientists use TACC systems to generate synthetic objects for robot training.
Deep-learning methods have the potential to offer substantially better results, generating superior representations for characterizing the human brain.
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 demonstrated a novel multifunctional ultrathin contact lens sensor layer with transistors that may revolutionise the manufacture of smart contact lenses.
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.
A new eye test may predict wet age-related macular degeneration, a leading cause of severe sight loss, three years before symptoms develop.
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"
An AI platform derives an optimal combination of available therapies against SARS-CoV-2 - the optimal drug therapy was a combination of the drugs remdesivir, ritonavir, and lopinavir at specific doses.
Using machine learning, a group of researchers demonstrated that it was possible to detect dementia from conversations in human-agent interaction.
Using machine learning, a team of Western computer scientists and biologists have identified an underlying genomic signature for 29 different COVID-19 DNA sequences.
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.
With the advent of pharmacogenomics, machine learning research is well underway to predict patients' drug response that varies by individual from the algorithms derived from previously collected data on drug responses.
Researchers have found that people who are asymptomatic for Covid-19 may differ from healthy individuals in the way that they cough.
An artificial intelligence-based detects early stages of Alzheimer’s through functional magnetic resonance imaging.
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 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 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.
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.
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.
Researchers have created a machine learning algorithm that can detect subtle signs of osteoarthritis on an MRI scan taken years before symptoms even begin.
Digital phenotyping and machine learning have emerged as promising tools for monitoring patients with psychosis spectrum illnesses.
Scientists have used machin -learning to organize the chemical diversity found in the ever-growing databases for the popular metal-organic framework materials.
Researchers explain how computer scientists and clinicians are trying to reduce fatal medical errors by building “ambient intelligence” into the spaces where patients reside.
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.
Scientists and collaborators are using machine learning to address two key barriers to industrialization of two-photon lithography.
This is the first known time that AI has used causation instead of correlations to support doctors with diagnosis in simulated cases.
Researchers develop new machine learning approach that shows promise in predicting Necrotizing enterocolitis; could lead to improved medical decision-making in neonatal ICUs.
Researchers have developed an algorithm that not only predicts hospital readmissions of heart failure patients, but also tells you why these occur.
Researchers have developed a technique based on self-learning algorithms that improves the performance of the controller by a factor ten.
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.
Bioengineers have designed a glove-like device that can translate American Sign Language into English speech in real time through a smartphone app.
Researchers caution that consumer wearables are not sophisticated enough to monitor the complicated illness.
The Fraunhofer IBMT is developing the miniaturized ultrasound system for automated monitoring of bladder irrigation.
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.
Improving the prediction of survival indicators in patients with breast cancer using tools from artificial intelligence and probabilistic modelling is the aim of ModGraProDep.