Educational Healthcare Analytics
AdmitGuard Intelligence is a full-stack data science platform designed to demonstrate modern machine learning integration in a secure, healthcare-style environment.
Project Purpose
This platform serves as a resume-grade portfolio project showcasing end-to-end ML engineering. It covers data preprocessing, predictive modeling, explainable AI (XAI), and secure API design within a Next.js and FastAPI architecture.
Dataset & Scope
The platform utilizes independent, de-identified datasets for clinical research. The scope includes separate tasks for predicting 30-day readmission risk (Logistic Regression) and estimating insurance claim amounts (Random Forest) using task-specific clinical data.
Security Design
Built with a "secure-by-default" mindset, the system employs strict Role-Based Access Control (RBAC), enforces Google OAuth for authentication, and validates all analytical inputs to prevent data poisoning or unauthorized access.
Important Limitations
This system is strictly for educational and analytical demonstration. It is not HIPAA compliant, does not provide medical diagnoses, and must never be used to replace professional clinical judgment or real hospital production systems.