Age-stratified multimodal MRI and machine learning to explore autism-related brain characteristics in youth - Top-Institutions - MDSpire

Age-stratified multimodal MRI and machine learning to explore autism-related brain characteristics in youth

  • By

  • Garazi Casillas Martinez

  • Anthony Winder

  • Kimberly Amador

  • Eneko Uruñuela

  • Matthias Wilms

  • Sarah J. MacEachern

  • Nils D. Forkert

  • July 2, 2026

  • 0 min

Share

Top Institutions in Neurology

Brief introduction explaining scope and methodology.

  • #1

    University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill

    Chapel Hill, North Carolina

    Key Differentiators

    • Neurology
    • Pediatrics

  • #2

    Yale University
    Yale University

    New Haven, Connecticut

    Key Differentiators

    • Neurology
    • Pediatrics

  • #3

    University of Pennsylvania
    University of Pennsylvania

    Philadelphia, Pennsylvania

    Key Differentiators

    • Neurology
    • Radiology

Original Source(s)

Age-stratified multimodal MRI and machine learning to explore autism-related brain characteristics in youth

  • by Garazi Casillas Martinez, Anthony Winder, Kimberly Amador, Eneko Uruñuela, Matthias Wilms, Sarah J. MacEachern, Nils D. Forkert

  • July 2, 2026

Related Content

Psychiatric and neurological predictors of early ADHD medication discontinuation across the lifespan: a multinational study

Autism Diagnosis Is Expanding — At a Cost

Autism may be overdiagnosed — and, Liao and Fombonne argue, that children with the greatest needs may be paying the price.

Electroencephalographic abnormalities and clinical phenotypes in children with autism spectrum disorder: a single center cohort study