03 · Academic classification and guidance
Diagnostic Care
Academic prototype exploring symptom classification and informational guidance with Flask and machine learning.
- Python
- Flask
- Random Forest
- JavaScript
- HTML
- CSS
Context
Problem
The team explored classification models in an educational symptom-guidance workflow.
The response
Solution
Flask application with a web interface, classification logic, data, and experimental integrations.
My contribution
Full-stack work and product decisions
Verifiable contributions to Flask, the interface, guidance logic, and project files.
Verified contribution: Public contributor with verifiable commits.
Important note
Academic prototype. It does not provide medical diagnoses or replace evaluation by healthcare professionals.
Key challenges
Complexity addressed
- Connect the model to an understandable interface.
- Communicate experimental results responsibly.
- Coordinate backend, frontend, and resources.
Outcomes
Value created
- Functional educational prototype.
- Integrated interface and classification flow.
- Basis for discussing responsible AI.