AI-Driven Autism Spectrum Disorder Detection System
This project focuses on the early detection of Autism Spectrum Disorder (ASD) in infants using advanced AI and deep learning techniques. Early identification enables timely intervention, significantly improving developmental outcomes.
Built with a modern React.js frontend and a robust AI-powered backend, the system analyzes behavioral patterns, visual cues, and interaction data to assist healthcare professionals in identifying early signs of autism with high accuracy.
The project aims to bridge the gap between technology and healthcare by delivering an intelligent, scalable, and reliable solution for early autism detection.
Key Highlights:
Winner –YIP 5.0 District Level Competition
Healthcare Innovation –Awarded for innovation in healthcare and early diagnosis
Deep Learning –AI-powered deep learning models for behavioral analysis
Data Insights –Data-driven insights using real-time and historical data
High Performance –Fast, scalable backend using modern APIs
Responsive UI –Clean, accessible, and responsive React.js UI
Continuous Learning –Continuously evolving with improved models and datasets
React.js
Tailwind CSS
JavaScript
FastAPI
Python
Deep Learning (CNN / RNN)
TensorFlow / PyTorch
Computer Vision
MongoDB
SQL (PostgreSQL / MySQL)
REST APIs
Data Annotation & Model Training
Git & GitHub
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