From brain scans to classifiers: A systematic review of ML-based autism diagnostic frameworks - Takeaways - MDSpire

From brain scans to classifiers: A systematic review of ML-based autism diagnostic frameworks

  • By

  • Naveed Ur Rehman Ahmed

  • Ayesha Tajammul

  • Afzal Badshah

  • Muhammad Saad

  • Abdulrahman Ahmed Gharawi

  • Ammar Almutawa

  • Sakher Ghanem

  • Ali Daud

  • June 27, 2026

  • 0 min

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  • 1

    Autism Spectrum Disorder (ASD) affects approximately 1 in 44 children in the United States and is diagnosed primarily through behavioral assessments.

  • 2

    Neuroimaging techniques, including MRI, fMRI, and EEG, provide objective insights into brain abnormalities associated with ASD.

  • 3

    Existing reviews on neuroimaging for ASD often focus on multiple conditions, limiting their applicability to ASD diagnosis specifically.

  • 4

    This review covers 107 key studies and emphasizes advancements in multimodal neuroimaging techniques for ASD diagnosis.

  • 5

    The article analyzes diagnostic performance metrics, including accuracy and Area Under the Curve (AUC), for various neuroimaging modalities.

Original Source(s)

From brain scans to classifiers: A systematic review of ML-based autism diagnostic frameworks

  • by Naveed Ur Rehman Ahmed, Ayesha Tajammul, Afzal Badshah, Muhammad Saad, Abdulrahman Ahmed Gharawi, Ammar Almutawa, Sakher Ghanem, Ali Daud

  • June 27, 2026

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