net/artificial-intelligence- machine-learning-can-be-used- to-predict-autism-in-children/
According to Sowmya Krishnan of Analytics Insight, Researchers from University of North Carolina at Chapel Hill and Washington School of Medicine reveal that autism can be predicted before 24 months and at a 96 percent accuracy rate. Published recently in http://stm.sciencemag.org/
content/9/393/eaag2882.full recently researcher Joseph Piven, professor of psychiatry, psychology and paediatrics at the University of North Carolina, Chapel Hill noted “we are always trying to detect autism at younger ages, so we can start treatment earlier, but we hit a wall around 2 to 3 years of age, because the symptoms don’t start showing up until around then” during an interview. For more Dr. Piven’s work: https://www.med.unc.edu/ psych/directories/faculty/ joseph-piven
The team developed and validated a machine learning algorithm and thereafter set up conditions to train the system “using the scans of the 6 month old infants and it correctly predicted 9 out of 11 infants who were diagnosed with autism at 24 months, with a sensitivity of 81.8%. Also the remaining 48 6-month old infants who were not diagnosed with ASD were correctly classified.”
Autism is a developmental disorder frequently associated with social interactivity difficulties, communication challenges and restrictive and repetitive behaviors. https://en.wikipedia.org/
Its usual onset is by 2 or 3 years of age. The prognosis is often poor and over 25 million are afflicted by the disease.
Autism studies can be found via National Institutes of Health Eunice Kennedy Shriver National Institute of Child Health and Human Development website.
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