
Artificial intelligence for emergency management
A consortium aims to develop a platform that will serve as the basis for novel services and test the use of new artificial intelligence tools.
Machine learning is a type of artificial intelligence that can be described as a mathematical model where computers are trained to learn to see connections and solve problems using different data sets.
A consortium aims to develop a platform that will serve as the basis for novel services and test the use of new artificial intelligence tools.
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.
Engineers use Frontera supercomputer to develop physics-informed neural networks for additive manufacturing.
Research using machine learning on images of everyday items is improving the accuracy and speed of detecting respiratory diseases, reducing the need for specialist medical expertise.
A new study could help scientists mitigate the future spread of zoonotic and livestock diseases caused by existing viruses.
Using fluoresence images from live cells, researchers have trained an artificial neural network to reliably recognize cells that are infected by adenoviruses or herpes viruses.
New technology could transform the ability to accurately interpret HIV test results, particularly in low- and middle-income countries.
Smartwatches and other wearable devices may be used to sense illness, dehydration and even changes to the red blood cell count.
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.
Neural network framework may increase radiologist's confidence in assessing the type of lung cancer on CT scans, informing individualized treatment planning.
Machine learning helps some of the best microscopes to see better, work faster, and process more data.
Researchers propose a deep learning-based model for mimicking and continuously modifying speaker voice identity during speech translation.
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.
Researchers have investigated how machine learning can be used to find effective testing methods during epidemic outbreaks, thereby helping to better control the outbreaks.
Powerful algorithms used by Netflix, Amazon and Facebook can ‘predict’ the biological language of cancer and neurodegenerative diseases like Alzheimer's.
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.
Researchers have created a machine learning model that helps identify bipolar disorder at earlier stages.
Researchers have developed clothing that uses special fibers to sense a person's movement via touch.
Scientists at Osaka University employed deep learning to improve mobile mixed reality generation.
Researchers have developed an AI platform that could one day be used in a system to assess vascular and eye diseases.
Using a special dye, cells are colored according to their pH, and a machine learning algorithm can detect changes in the color spectrum due to cancer.
Researchers have developed a machine learning-based technique that speeds speeds up calculations of drug molecules' binding affinity to proteins.
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.
A machine learning algorithm helps accurately differentiate benign and premalignant colorectal polyps on CT colonography scans.
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.
Researchers have used "federated learning" to examine electronic health records to better predict how COVID-19 patients will progress.
Researchers have developed smartphone-based apps that solve the biggest problems for people with hearing loss: filtering out background noise and improving speech perception.
Deep-learning methods have the potential to offer substantially better results, generating superior representations for characterizing the human brain.
Researchers have developed a new photonic processor that could revolutionize artificial intelligence.
Researchers are creating a smart port to the brain that will use artificial intelligence to selectively stimulate tissue regrowth and seizure intervention.
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"
A device could help scientists better understand the health benefits of outdoor lighting and lead to wearables that could nudge users to get more outdoor time.