A Deep Learning–driven Intelligent Framework For Automated Prediction And Detection Of Autism And Adhd

Abstract

Autism Spectrum Disorder (ASD) And Attention Deficit/Hyperactivity Disorder (ADHD) Are Neuro Developmental Conditions That Affect The Cognitive Behavior, Attention, And Social Interaction. Early And Accurate Identification Is Essential For A Effective Intervention; However, Traditional Diagnostic Of A Approaches Often Rely On Subjective Clinical Assessments. This Paper Proposes A Computational Framework For The Automated Screening Of Autism And ADHD. The System Analyzes Facial Images For Autism Detection And MRI Brain Images For ADHD Detection Using Structured Analytical Methods. In Addition, Behavioral Screening Tests Have A Such As Camera-based Observation, Speech Pattern Analysis, And Questionnaire-based Evaluation Are Integrated To Support Clinical Assessment. The Framework Is Implemented As A Web-based Platform That Enables Data Upload, Automated Evaluation, And Report Generation. The Proposed System Aims To Assist Early Identification, Support Clinical Decision-making, And Improve Accessibility To Neuro Developmental Disorder Screening.

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