Project Overview
ASDM (Autism Spectrum Disorder Monitor) is a web-based screening tool that uses machine learning to assist in early detection of autism spectrum disorders. The application provides accessible, non-invasive screening capabilities to help identify potential developmental concerns.
Flask
Machine Learning
Python
Web Development
Healthcare
Data Analysis
Key Features
- Automated Screening: ML-powered assessment of behavioral indicators
- User-Friendly Interface: Intuitive web application for easy access
- Privacy-Focused: Secure data handling and confidentiality protection
- Evidence-Based: Built on established screening methodologies
- Accessibility: Designed for use by parents, caregivers, and healthcare providers
- Educational Resources: Information and guidance for users
Technical Implementation
The application combines web development with machine learning to create an accessible screening tool:
- Flask Backend: Python web framework for server-side processing
- ML Model: Trained on behavioral assessment data for pattern recognition
- Web Interface: Responsive design for desktop and mobile access
- Data Processing: Secure handling of user input and assessment results
- Result Analysis: Comprehensive reporting and recommendation system
- Database Integration: Secure storage of assessment data and results
Machine Learning Approach
The ML component includes:
- Feature extraction from behavioral assessment questionnaires
- Supervised learning models trained on validated screening data
- Risk stratification and probability scoring
- Continuous model validation and improvement
- Interpretable results for healthcare professionals
Project Impact
ASDM contributes to healthcare accessibility by:
- Providing early screening capabilities in underserved areas
- Reducing barriers to initial assessment
- Supporting healthcare providers with screening tools
- Educating families about developmental milestones
- Facilitating timely intervention and support
Future Enhancements
Planned improvements include:
- Integration with electronic health records
- Multi-language support for diverse populations
- Mobile app development for increased accessibility
- Advanced analytics for population health insights
- Telemedicine integration capabilities