JUN 08, 2017 03:16 PM PDT

AI Predicts Autism in Infants

WRITTEN BY: Xuan Pham

A type of artificial intelligence is so well-trained on autistic brains that researchers say the technology can predict whether babies, as young as 6-months-old, will develop autism.

Image credit: pixabay.com

This is not the first time such technology has been used to predict autism in young children. In February, researchers from the University of North Carolina-Chapel Hill leveraged structural MRI data from 2-year-olds to predict, with 80 percent accuracy, the likelihood that the children will develop autism later in life.

The same group of researchers now tweaked their AI - this time using machine learning techniques based on the brain’s functional connections. When applied to the brain scans of 6-month-old infants, the AI correctly predicted a diagnosis of autism at 24 months of age.

"It was extremely accurate," said Robert Emerson, the study’s lead author of the group’s AI technology. Of the 59 infants, the AI had 100 percent accuracy in predicting that 48 infants would not develop the disease. Of the 11 infants later developed autism at 24 months, the machine predicted 9 cases. In the study, all the infants were considered high-risk, which meant that they had an older sibling who was also diagnosed with autism. “It did miss two kids, so it might be that their particular type of autism wasn’t represented in the behavioral profile we used to pick out the brain connections,” says Emerson.

As part of this current study, the researchers used functional connectivity MRI (fcMRI) to scan the infants’ brains while they slept. Each scan measured the activity of over 26,000 neural connections over hundreds of brain regions, including those that are responsible for characteristic autism features, such as language, motor development, and repetitive behavior. At 24 months, the children’s brains were scanned again, and they also received behavioral and clinical assessments.

The results show that the machine-learning algorithm could tease apart the functional connections associated with autism. That is, the AI learned how activity from one region of the brain interacts with another region, and these patterns can be diagnostic of autism early on.

Thus, with both structural and functional data to map autism in the brain, the team may have just created one of the most powerful and sensitive tools to diagnose autism in children.

"The idea is that we can be more effective if we can get to these kids before they develop autism, perhaps ameliorating or preventing it," said Dr. Joseph Piven, the study’s senior investigator.

“It’s going to be really important to use machine learning in the future to pull all these pieces of information together,” said Emerson. If they can combine data from the brain, behavior, and environmental exposures, Emerson believes “we’re going to have a very good shot at really nailing this early prediction.”

Additional source: Live Science

About the Author
  • I am a human geneticist, passionate about telling stories to make science more engaging and approachable. Find more of my writing at the Hopkins BioMedical Odyssey blog and at TheGeneTwist.com.
You May Also Like
APR 21, 2018
Cardiology
APR 21, 2018
Scientists Recommend Exercise After A Heart Attack
Doctors recommend regular physical activity to reduce the risk of a heart attack, but the same advice applies even after a person has a heart attack. A new...
MAY 04, 2018
Clinical & Molecular DX
MAY 04, 2018
New Blood Test Detects Peanut Allergy with 98% Specificity
A new blood test trumps traditional diagnostic methods for determining peanut allergy, the most common allergy for children. From the Medical Research Coun...
JUN 14, 2018
Clinical & Molecular DX
JUN 14, 2018
Automated Blood Drawing Device Coming to Your Doctor's Office
A robot arm could soon be coming to your doctor’s office to take your blood and analyze it for you. From scientists at Rutgers University, this techn...
AUG 01, 2018
Cell & Molecular Biology
AUG 01, 2018
Levels of One Molecule, LAC, can Diagnose Depression
Depression can be hard to classify and therefore, challenging to treat. New work could help change that....
AUG 22, 2018
Clinical & Molecular DX
AUG 22, 2018
New Clinical Assay Useful For Urothelial Cancer
U.S. Food and Drug Administration (FDA) has now approved a pharmDx assay called ‘Dako PD-L1 IHC 22C3’ by Agilent Technologies Inc. for use in u...
AUG 22, 2018
Clinical & Molecular DX
AUG 22, 2018
Biomarker Predicts Kidney Cancer
A research study led by Beth Israel Deaconess Medical Center has discovered a tumor biomarker that could be used to determine the onset of renal cell carci...
Loading Comments...