Using artificial intelligence technology, researchers have identified both risk and protective factors for depression in middle-aged to older adults. Social isolation, the study found, was the biggest risk factor for depression, followed by mobility difficulties and health issues.
Experimental observations conclude learning is mainly performed by neural dendrite trees as opposed to modifying solely through the strength of the synapses, as previously believed.
A new deep learning algorithm utilizes neuroimaging data to differentiate between Parkinson's disease and other parkinsonian syndromes such as PSP and multiple systems atrophy.
Using MEG data, a new AI algorithm called AI-MIND is able to assess dementia risk and the potential effectiveness of treatments for depression, researchers say.
Researchers have developed a new AI algorithm that prevents smart devices such as Alexa or Siri from correctly hearing your words 80% of the time. The algorithm is a step toward providing personal agency in protecting the privacy of their voice in the presence of smart devices.
Researchers trained an AI to determine which psychotropic agent a zebrafish had been exposed to based on the animal's behaviors and locomotion patterns.
A new AI algorithm can predict whether a person is on the autism spectrum by examining their brain scans. The algorithm can also predict the severity of symptoms and could be used as an early detection tool for ASD.
A new computational model uses the entire function of the brain rather than specific networks or areas to explain the relationship between mental processing and brain anatomy. The model aims to discover how the brain works and breaks down as a result of aging and dementia.
Combining AI and robotics technology, researchers have identified new cellular characteristics of Parkinson's disease in skin cell samples from patients.