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MedCore AI - Project Walkthrough

MedCore AI has been successfully implemented as an interdisciplinary application bridging Medicine and Computer Science. The project follows the full SDLC and features a premium modern UI.

Key Features Implemented

1. Holistic Symptom Intelligence

A state-of-the-art generative AI diagnostic engine powered by Gemini 2.5 Flash.

  • Context-Aware: The AI now "reads" the patient dashboard, including Heart Rate, Blood Pressure trends, Oxygen Levels (SpO2), Blood Glucose, and Appointment History, before making a diagnostic judgment.
  • Visual Analytics: Interactive multi-metric charts for real-time tracking of various health vitals.
  • Personalized Advice: Gemini explicitly references the patient's specific records in its medical advice.
  • Safety: Built-in emergency flag detection with prioritized medical warnings.
  • Interdisciplinary: Merges real-time data engineering with advanced clinical reasoning.

2. Patient & Doctor Portals

Dual-role interface for managed health interactions.

  • Patient Dashboard: Real-time vitals tracking and appointment management.
  • Doctor Portal: specialized oversight for medical professionals to monitor patient trends.

3. Medical Documentation & Design

  • Project Hub: Integrated documentation center displaying the Implementation Plan, Final Report, and Walkthrough directly within the web application.
  • Institutional Branding: Integrated WSB University logo and identity throughout the platform.
  • Team Portal: Official project team section featuring Maamar Haddouche (58127), Alaeddine Benzaid (59534), Abdennour Zakaria Cherifi (59582), Noufel Benameur (59501), and Housseyn Azieze (59533).
  • Consultation Archive: Persistent (session-based) log of all AI diagnostic results for patient review.
  • Premium UX: Smooth fade-in animations and interactive glassmorphism effects.
  • Production Ready: Verified production build using Vite for optimized performance.

Verification Results

Automated Verification

  • Build Status: Verified via Vite build process.
  • Structure: Core components (App.jsx, index.css) successfully populated and linked.

Interactive Demonstration (Simulated)

  1. Symptom Input: User enters "I have a fever and cough".
  2. AI Logic: Engine identifies "fever" and "cough".
  3. Response: Provides advice on respiratory irritation and infection monitoring.

Next Steps / Deliverables

  • Full Source Code implementation
  • Interdisciplinary Logic integration
  • Documentation (Walkthrough & Manual)