Project Overview

Many parents miss the critical "golden time" to detect early signs of autism, delaying the opportunity for timely intervention and personalized care.

Benefits of
Early Detection for Autism

Early detection of Autism Spectrum Disorder (ASD) is crucial for improving a child’s communication skills, social interactions, and overall quality of life. Research highlights several benefits of identifying and addressing autism during critical developmental windows, such as infancy and early childhood.

essential social &
verbal communication skills

cognitive & adaptive skills

Children who receive early intervention (before age 3) show a 50% higher likelihood of developing essential social and verbal communication skills than those diagnosed later. 

(Source: National Institutes of Health)

children with autism who participate in early intervention programs for 1-2 years demonstrate a 30-50% improvement in cognitive and adaptive skills compared to those who begin treatment after age 5. (Source: Centers for Disease Control and Prevention, CDC)

Early Start Denver Model (ESDM), a leading intervention for toddlers, has been shown to result in a 67% improvement in IQ and adaptive behaviors when initiated before age 3.

References:The Effects of Early Intervention on Social Communication Outcomes for Children with Autism Spectrum Disorder: A Meta-analysis(2020) / Early Identification and Interventions for Autism Spectrum Disorder: Executive Summary(2015) / Early Behavioral Intervention Is Associated With Normalized Brain Activity in Young Children With Autism(2012)

What Stops Early Detection?

Diagnostic
Overshadowing

Children are often first diagnosed with conditions like ADHD or sensory processing issues, which can mask underlying autism spectrum disorder (ASD). This leads to delays in appropriate interventions.

Emotional
Denial

Many parents struggle to accept the possibility that their child might have autism, fearing social stigma, lifelong challenges, or an uncertain future.
Some may dismiss early signs as "just a phase" or compare their child to others who developed social skills later.

Systemic
Barriers

Challenges within healthcare and educational systems, such as long waiting periods for evaluations, communication gaps between providers, and authorization difficulties, contribute to delayed diagnoses.

References: Why Autism Diagnoses Are Often Delayed, Family Denial of Autism, Timeliness of Autism Spectrum Disorder Diagnosis and Use of Services among U.S. Elementary School-Aged Children

User Flow Diagram:
Before Making an Appointment
with the Specialist

User Journey

Using Machine Learning + Deep Learning
to Detect Autism in High Accuracy

Step 1: Data Collection → Parents upload videos, text descriptions, and behavioral observations.

Step 2: Feature Extraction → AI extracts key features (e.g., gaze tracking, repetitive actions, verbal responsiveness).

Step 3: Model Prediction → ML algorithms analyze patterns and classify ASD risk levels.

Step 4: Personalized Insights → The system provides customized recommendations for early intervention.

By combining multiple ML models, this system increases detection accuracy and helps parents take early action for their child's development.

Building trust between Users and Technologies

General AI : provides broad autism insights, helping parents recognize common ASD behaviors through standardized data. However, it lacks individual accuracy and may lead to misinterpretation.

Personalized Machine Learning : continuously adapts to a child’s unique behaviors, reducing errors and providing customized, real-time insights for parents.

Why It Builds Trust?

1. Learns from daily child-specific data, making recommendations more relevant.

2. Enhances parent-child communication by offering tailored intervention strategies.

3. Creates a trust loop—the more parents engage, the more accurate and helpful AI becomes. Personalized AI bridges the gap between general knowledge and real-world application, ensuring autism detection is both precise and actionable.