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.
Scientists used brain-computer-interface to train the brains of patients to reduce phantom-hand pain.
Researchers found that a game could help scientists understand how second language learners learn a new language, and could even help them learn it faster.
States that resemble sleep-like cycles in simulated neural networks quell the instability that comes with uninterrupted self-learning in artificial analogs of brains.
A study finds that people are aware of surprisingly limited color in their peripheral vision; much of our sense of a colorful visual world is likely constructed by our brain.
A new AI approach classifies a common type of brain tumour into low or high grades with almost 98% accuracy, researchers report.
Researchers have developed a system for integrating artificial chip-based 'neurons' with real neurons using QR-code-like patterns of light to facilitate communication.
Researchers have developed an AI algorithm that can detect and identify different types of brain injuries.
A researcher has developed ultra-light tattoo electrodes that are hardly noticeable on the skin and make long-term measurements of brain activity cheaper and easier.
Brain cancer patients in the coming years may not need to go under the knife to help doctors determine the best treatment for their tumors.
Next-generation brain implants with more than a thousand electrodes can survive for more than six years.
Engineers are working on developing soft, flexible neural implants that can gently conform to the brain’s contours and monitor activity over longer periods.
Scientists have developed an innovative new technique that uses artificial intelligence to better define the different sections of the brain in newborns during a magnetic resonance imaging (MRI) exam.
Scientists have developed a technique for visualising the structures of all the brain's blood vessels including any pathological changes.
The UNC School of Medicine lab of Jason Franz, PhD, created virtual reality experiments to show how a potentially portable and inexpensive test could reduce falls and related injuries in people with multiple sclerosis.
Researchers demonstrated a methodology that combines the bioprinting and imaging of glioblastoma cells in a way that more closely models what happens inside the human body.
Using a robot to treat brain aneurysms is feasible and could allow for improved precision when placing stents, coils and other devices.
A non-invasive, wearable, magnetic brain stimulation device could improve motor function in stroke patients.
New machine learning study suggest the presence of at least nine gender “expressions”.
Researchers at Georgia Tech have now developed a chip that accurately replicates its function using the human cells that form this important part of our anatomy.
Research confirms the efficiency of using computer-based programmes and virtual reality for improving children's attention and social skills.
Artificial intelligence may soon play a critical role in choosing which depression therapy is best for patients.
The first Parkinson's patient worldwide was treated with a new neurostimulator, which enables better, more personalized care for patients.
Researchers have designed and developed three digital games to help children and adults improve their cognitive skills.
Researcher have developed a computer method that uses MRI and machine learning to rapidly forecast genetic mutations in glioma tumors,
Researchers have found that virtual reality may interfere with visual memory.
A novel method of combining advanced optical imaging with an artificial intelligence algorithm produces accurate, real-time intraoperative diagnosis of brain tumors.
Researchers designed a video game to improve mindfulness in middle schoolers and found that when young people played the game, they showed changes in areas of their brains that underlie attention.
Deep learning can boost the power of MRI in predicting attention deficit hyperactivity disorder (ADHD).
