Tag: machine learning in neuroimaging

Researchers have developed an interpolation-based method that generates synthetic MRI training data between age- and gender-matched participants from different scanners, ...

The study's design reflects a broader tension in neuroimaging research between model complexity and data availability. Task-based fMRI experiments typically ...

A UK Biobank study of 46,843 people shows that genetic risk and lifestyle jointly drive MRI-based brain aging, with a ...

A new peer-reviewed study compares three deep learning approaches for detecting stroke lesions on contrast-free MRI, finding that the self-configuring ...

A new study shows that an AI brain age model trained on mortality risk from MRI scans mediates how health ...

When scientists scan the brains of people who have meditated for years, they typically look for one thing: which networks ...

Tau buildup in a handful of specific brain regions may signal which people with mild cognitive impairment will go on ...

A groundbreaking study published in Nature Communications is reshaping our understanding of brain development during preadolescence, shedding light on how ...

In a groundbreaking study poised to reshape our understanding of brain health and neurodiversity, researchers have unveiled an extensive set ...

In a groundbreaking study published in Translational Psychiatry, researchers have unveiled new insights into the neurobiological underpinnings of Attention Deficit ...