Yale School of Medicine Receives $27.7 Million Grant Toward Autism Research
NEW HAVEN COUNTY, CONNECTICUT, JUL 8 – The AI tool reduces autism and ADHD diagnosis time from months to minutes with 71.5% accuracy, enabling earlier intervention and personalized care, researchers said.
- On July 8, 2025, Yale School of Medicine received a $27.7 million grant from ARIA to develop interdisciplinary autism research focused on brain modeling and therapies.
- This grant supports collaboration among more than 30 Yale experts and responds to urgent needs due to current unmet demands for effective, personalized autism care.
- Concurrently, researchers published a new AI-based diagnostic method to rapidly assess autism and ADHD using invisible movement biomarkers, advancing earlier intervention possibilities.
- The AI study, led by an interdisciplinary team including Jorge José, shows diagnosis could be done in as little as 15 minutes by analyzing motion fluctuations invisible to the naked eye.
- Together, these efforts aim to improve treatment accuracy and timeliness and facilitate new therapies that could transform neurodevelopmental disorder care nationwide.
35 Articles
35 Articles
New study identifies four distinct autism subtypes with unique genetic signatures
Autism is classified as a 'spectrum' for a reason: Each case is different. Scientists have struggled to parse through the many ways autism can manifest, much less to link these varying observable traits (called phenotypes) to underlying genetics.
A Strange Little Bird
You’ve Always Been This Way is a column written by Taylor Harris, a late-diagnosed neurodivergent woman and 1980s preschool dropout, who identifies every moment from her past that filled her with shame, and mutters, “Yep, that tracks. I see it all now.” - - -Before 2013, no one could be autistic and have ADHD. Back then, the DSM followed the one-drop rule for neurodevelopmental conditions. Got a touch of the ’tism? It is settled, then. No hypera…
Leveraging artificial intelligence for diagnosis of children autism through facial expressions
The global population contains a substantial number of individuals who experience autism spectrum disorder, thus requiring immediate identification to enable successful intervention approaches. The authors assess the detection of autism-related learning difficulties in children by evaluating deep learning models that use transfer learning methods along with fine-tuning methods. Using autism spectrum disorder (ASD) diagnosed child RGB images data…

Yale School of Medicine Receives $27.7 Million Grant Toward Autism Research
NEW HAVEN, Conn., July 8, 2025 /PRNewswire/ -- Yale School of Medicine (YSM) was awarded a $27.7 million grant from Aligning Research to Impact Autism (ARIA) to develop an interdisciplinary research project to investigate non-invasive functional communication methods through large-scale…
AI used to improve speed and accuracy of autism and ADHD diagnoses
It can take as long as 18 months for children with suspected autism spectrum or attention-deficit-hyperactivity disorders to get a diagnostic appointment with a psychiatrist in Indiana. But an interdisciplinary team led by an Indiana University researcher has developed a new diagnostic approach using artificial intelligence that could speed up and improve the detection of neurodivergent disorders.
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