Researchers have developed a new artificial intelligence tool that is able to automatically measure the amount of fat around the heart from MRI scan images.
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This overview introduces smart insulin delivery systems and more innovations that help patients and doctors guide decision-making in diabetes care.
Researchers are using generative adversarial networks to improve brain-computer interfaces for people with disabilities.
Google set it sigths to transform the healthcare industry through the use of cloud technologies and machine learning.
Chatbots hold promise for dementia patient or caregiver support, but are still in their infancy, new research finds. None of the interactive digital apps tested performed well on all testing criteria.
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.
Wearables are becoming a trend in respiratory care and many products are being developed to monitor patients remotely. But how much can these tools really help clinicians?
Electronic skins will play a significant role in monitoring, personalized medicine, prosthetics, and robotics.
An AI-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy.
Data privacy and security concerns hamper large-scale studies. Researchers have developed a potential solution.
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.
E-mental health services could provide a response to these challenges and offer effective ways for prevention, diagnosis, treatment, and aftercare.
The benefits people could reap from exoskeletons rely heavily on having time to train with the device.
Scientists have developed a bio-compatible implantable AI platform that classifies in real time healthy and pathological patterns in biological signals.
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.
Graphene represents incredible opportunities for advancement in many fields, including medical science.
Researchers examined people’s emotional response to cloned faces, which could soon become the norm in robotics.
To enhance human-robot collaboration, researchers at Loughborough University have trained an AI to detect human intention.
A deep learning-based technique can be used to eliminate the need for special stains to be prepared by human histotechnologists.
A team of researchers at Washington University School of Medicine have developed a deep learning model that is capable of classifying a brain tumor as one of six common types using a single 3D MRI scan.
A new approach to tackling the spread of malaria in sub-Saharan Africa, which combines affordable, easy-to-administer blood tests with machine learning and unbreakable encryption, has generated encouraging early results in Uganda.
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.
Scientists have created a deep learning method, RoseTTAFold, to provide access to highly accurate protein structure prediction.
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.
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.
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.
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 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.
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.
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.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days.
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.
Professor Dr Henning Windhagen is a great fan of semi-automatic systems in the OR that help with implants but leave the surgeon in the driver’s seat.
Researchers combined motion analysis that uses smartphone application and machine learning that uses an anomaly detection method, thereby developing a technique to easily screen for carpal tunnel syndrome.
Many patients use their inhalers and insulin pens wrong. Researchers have developed a system to reduce those numbers for some types of medications.
Using AI and mobile digital microscopy, researchers hope to create screening tools that can detect precursors to cervical cancer in women in resource-limited settings.
Researchers have developed system for smart speakers to monitor both regular and irregular heartbeats without physical contact.
Researchers have succeeded in making an AI understand our subjective notions of what makes faces attractive.
The Fraunhofer Institutes project M³Infekt aims to develop a multi-modal, modular and mobile system of sensors for monitoring infectious diseases.
The Covid-19 pandemic highlights how remote healthcare robots currently being developed could be beneficial in the future.
Researchers at the Indian Institute of Science and SigTuple Technologies have developed a method to measure hemoglobin levels in small-volume blood samples.
Deep learning-based system enables dermatologist-level identification of suspicious skin lesions from smartphone photos, allowing better screening.
Dr Jan Stallkamp has a vision: robots that can treat patients more efficiently and more precisely than any human physician.
Researchers have constructed a 3D vision-guided artificial skin that enables tactile sensing with high performance, opening doors to innumerable applications in medicine.
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.
Professor Dr Peter Pott and his team turn to 3D printers to successfully realize his vision of “high end at low cost” medical devices.
Using theoretical calculations, scientists showed that it would not be possible to control a superintelligent AI.
Physicians who follow AI advice may be considered less liable for medical malpractice than is commonly thought, according to a new study of potential jury candidates in the U.S.
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"
Is it possible to read a person's mind by analyzing the electric signals from the brain? The answer may be much more complex than most people think.
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.
Researchers have enabled a quadriplegic man to control a pair of prosthetic arms with his mind.
Robots may have some of these soft skills thought to be vital for successful leadership as they enable leaders to motivate, unite and inspire their employees.
An analysis highlights the realistic pros and cons of apps and other technologies that use AI to benefit older adults, including those facing dementia and cognitive decline.
Researchers have developed an AI tool that can measure the volume of cerebral ventricles on MRIs in children within about 25 minutes.
Researchers have developed a way for deep learning neural networks to rapidly estimate confidence levels in their output.
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.
Designers who use ethics to shape better companion robots will end up making better humans, too, say UNSW researchers.
Researchers have found that people who are asymptomatic for Covid-19 may differ from healthy individuals in the way that they cough.
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.
Researchers have developed a robotic exoskeleton that improves the lives of people with limited or no ability to move due to neurological and/or physiological disorders.
For the first time doctors have shown that measuring changes in 24-hour heart rate can reliably indicate whether or not someone is depressed.
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.
The development of new medical technologies based on cutting-edge discoveries has accelerated during the coronavirus pandemic.
A dose of artificial intelligence can speed the development of 3D-printed bioscaffolds that help injuries heal.
AI experts report that they have successfully addressed a major obstacle to increasing AI capabilities.
Researchers make the case that Artificial Intelligence tools have the potential to help researchers separate the wheat from the chaff.
Artificial intelligence is developing at an enormous speed and intelligent instruments will profoundly change surgery and medical interventions.
Researchers explain how computer scientists and clinicians are trying to reduce fatal medical errors by building “ambient intelligence” into the spaces where patients reside.
Although true “cyborgs” — part human, part robotic beings — are science fiction, researchers are taking steps toward integrating electronics with the body.
Loss of strength and muscle wastage is currently an unavoidable part of getting older and has a significant impact on health and quality of life.
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.
In the next-generation operating room interconnected sensors will collect data, analyse it in real-time and make it available to digital assistance functions.
Scientists and collaborators are using machine learning to address two key barriers to industrialization of two-photon lithography.
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 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.
Research shows how so-called “critical states” can be used to optimize artificial neural networks running on brain-inspired neuromorphic hardware.
Researchers have developed a machine learning model that can predict chemotherapy-associated nephrotoxicity.
The Fraunhofer IBMT is developing the miniaturized ultrasound system for automated monitoring of bladder irrigation.
Improving the prediction of survival indicators in patients with breast cancer using tools from artificial intelligence and probabilistic modelling is the aim of ModGraProDep.
Researchers are collaborating with local partners to establish a network of portable, handheld ultrasound scanners that can soon accelerate COVID-19 diagnosis.
Scientists are launching a project to apply machine learning methods to assess the role of climate variables in disease transmission
Researchers at King’s College London, Massachusetts General Hospital and health science company ZOE have developed an AI diagnostic that can predict whether someone is likely to have COVID-19 based on their symptoms.