- In new research presented at the Radiological Society of North America’s annual meeting, researchers used artificial intelligence to review brain scans of adolescents with and without attention deficit hyperactivity disorder (ADHD).
- This approach identified differences in the white matter tracts of the brains of individuals with ADHD, providing further insights into the condition.
- ADHD affects around 6 million children and teenagers in the United States, making early diagnosis and intervention crucial for improved well-being in a society increasingly influenced by distractions.
Attention deficit hyperactivity disorder (ADHD) can cause difficulty in maintaining attention, managing energy levels, and controlling impulses.
It typically shows up in childhood and can significantly affect an individual’s well-being and their ability to function in society.
In the United States, approximately
Experts say diagnosing ADHD can be challenging with medical professionals often relying on self-reported surveys that are subjective in nature. They say there is a clear demand for more objective methods of diagnosis.
In new research presented at the Radiological Society of North America’s annual meeting in November, scientists reported on a deep learning type of artificial intelligence (AI) to examine MRI scans of teenagers with and without ADHD.
The researchers said they discovered important differences in certain brain structures called white matter tracts in people with ADHD.
The researchers said that their study, which hasn’t been published yet in a peer-reviewed journal, is important because it’s the first to utilize deep learning to identify indicators of ADHD.
Deep learning is a type of AI that can automatically recognize patterns and connections within vast amounts of data.
Justin Huynh, MS, a study co-author and a researcher in the Department of Neuroradiology at the University of California…
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