<ul data-eligibleForWebStory="true"><li>The prevalence of Autism Spectrum Disorder (ASD) has rapidly increased, impacting communication, behavior, and focus.</li><li>Current diagnostic techniques for ASD are time-intensive and costly.</li><li>An AI-powered assistive technology is introduced to streamline ASD diagnosis and management.</li><li>The system integrates transfer learning with eye gaze variables to diagnose ASD.</li><li>This technology allows for in-home periodical diagnosis, reducing stress for individuals and caregivers.</li><li>User privacy is maintained through the use of image transforms.</li><li>The proposed method enhances communication between guardians and therapists for progress updates and support needs.</li><li>The approach ensures timely, accessible diagnosis while protecting privacy and improving outcomes for individuals with ASD.</li></ul>

Exploring Image Transforms derived from Eye Gaze Variables for Progressive Autism Diagnosis

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