University of Wollongong in Dubai — CSIT321

The 1st Dual-Engine
Telemedicine Platform

Xpert merges deep-learning diagnostics with immersive AR visualization and adaptive learning to transform how medical students understand pneumonia.

View Our Journey →
2
AI Engines
3D
AR Visualization
RAG
Knowledge Base
5
Team Members
About the Platform

What is Xpert?

A dual-engine telemedicine platform that combines CNN-powered pneumonia detection with an intelligent educational layer and AR visualization.

The Problem

Current pneumonia detection tools offer static 2D predictions with no educational context. Medical students lack immersive tools to understand pathology progression and clinical reasoning.

Our Solution

Xpert combines a dual AI pipeline (U-Net segmentation + DenseNet classification) with AR-powered 3D visualization and an adaptive learning engine. The platform doesn't just detect pneumonia — it teaches, explains, and adapts to each student's competency level through Grad-CAM heatmaps, a RAG-powered chatbot, and the MAPE-K feedback framework.

Who Is It For?

Medical students learning through AI-guided simulation, physicians using AR visualization for deeper case analysis, and general practitioners needing quick diagnostic reference overlays.

Core Features

Dual-Engine Architecture

Six integrated modules that power the Xpert experience from upload to insight.

AI Inference Pipeline

CLAHE enhancement, U-Net segmentation, and DenseNet121 classification with CheXNet weights. End-to-end inference under 5 seconds.

Grad-CAM Heatmaps

Gradient-weighted class activation maps that highlight clinically relevant regions on the X-ray for transparent, explainable diagnostics.

3D AR Visualization

Unity-powered AR rendering of lung anatomy with heatmap overlays, bounding boxes, and interactive 3D manipulation via WebGL.

RAG Knowledge Base

ChromaDB vector storage with Gemini 2.5 Flash for grounded, citation-backed medical responses with built-in hallucination prevention.

Adaptive Learning Engine

MAPE-K framework that tracks student performance, identifies competency gaps, and generates personalized clinical reports.

RBAC & Security

Student vs. Admin role separation, token-based authentication, PII-safe logging, and OWASP Top 10 compliance.

Built With

Technology Stack

Python FastAPI TensorFlow U-Net DenseNet121 Grad-CAM Unity WebGL ChromaDB Gemini 2.5 Flash SQLite Playwright k6 Docker Figma OpenCV
Platform Preview

See Xpert in Action

Interface screenshots from the working prototype.

Xpert Interface Demo
Main Interface
Student Chat Interface
Student AI Chat Interface
Doctor Chat Interface
Doctor Chat Interface
Student Report
Student Performance Report
AR Visualization
3D AR Lung Visualization
Dual Platform Overview
Dual-Platform Architecture Overview
The People Behind Xpert

Meet the Team

Five developers, designers, and engineers from the University of Wollongong in Dubai, building the future of medical education.

Islam Al-Mamoori

Islam Al-Mamoori

Project Lead, Frontend & Cybersecurity

Builds the student and doctor web portals, role-based UI, file upload flows, and real-time processing indicators. Enforces platform security through RBAC, PII protection, and OWASP-compliant hardening.

ID: 8540688
Yahya Kanjo

Yahya Kanjo

Code Lead & AI Specialist

Leads technical enforcement, repository administration, AI pipeline validation, RAG integrity testing, and Grad-CAM heatmap verification.

ID: 8490752
Muhammad Raza

Muhammad Raza

Data Engineer

Manages database architecture, medical dataset pipelines, ChromaDB vector storage, and data integrity across the full inference workflow.

ID: 8073545
Ibraheem Ahmad

Ibraheem Ahmad

3D & AR Engineer

Develops the Unity AR visualization system, converting AI outputs into interactive 3D lung models with heatmap overlays and WebGL rendering.

ID: 8550438
Celine Daou

Celine Daou

Marketing & UX Specialist

Leads user research, validation surveys, heuristic usability evaluations, and Xpert's visual branding and demo presentation strategy.

ID: 8309991

Project Supervisor

Dr. Milan Dordevic

University of Wollongong in Dubai

Xpert team with Dr. Milan Dordevic

The Xpert team with Dr. Milan Dordevic

Project Timeline

Our Milestones

From feasibility study to final demo — every step of our journey building Xpert.

October 2025
Deliverable 1 — Planning & Feasibility Analysis
Completed the initial feasibility study covering technical, economic, operational, and scheduling feasibility. Defined the project scope, stakeholder analysis, and risk assessment. Established that CNN-based pneumonia detection augmented with AR/VR is both technically achievable and educationally valuable.
Feasibility Study Risk Assessment Stakeholder Analysis
November 2025
Deliverable 2 — Requirements Analysis
Produced the System Requirements Specification (SRS) report. Defined all functional requirements (authentication, AI inference, AR visualization, adaptive engine, reporting) and non-functional requirements (performance, security, usability). Created use case diagrams and data flow specifications.
SRS Document Use Cases Functional Requirements
November 2025
Proof of Concept & Figma Prototype
Developed the interactive Figma prototype demonstrating the full user journey from login to AR visualization. Created the PoC presentation showcasing the technical architecture and UI/UX direction for the platform.
Figma Prototype PoC Presentation UI/UX Design
November – December 2025
Deliverable 3 — Design Document
Produced the comprehensive design document covering system architecture, database schema, API contracts, AI pipeline design (U-Net + DenseNet + Grad-CAM), AR visualization payload structure, and the MAPE-K adaptive learning framework.
Architecture Design Database Schema API Contracts AI Pipeline Design
January – February 2026
Development & Implementation
Built the core platform: FastAPI backend, dual AI inference pipeline (CLAHE preprocessing → U-Net segmentation → DenseNet121 classification), Grad-CAM heatmap generation, ChromaDB-powered RAG chatbot with Gemini 2.5 Flash, Unity 3D AR visualization client, and the MAPE-K adaptive learning engine with competency gap analysis.
Backend Development AI Pipeline AR Visualization RAG Chatbot
February 2026
Developer Security Policy
Established and enforced the Developer Security Policy aligned with ISO/IEC 27001:2013 and OWASP guidelines. Implemented mandatory MFA, environment variable management, branching strategy with PR-based code reviews, input validation, and PII protection protocols.
Security Policy ISO 27001 OWASP Compliance
February 2026
Test Plan & Quality Assurance
Delivered the comprehensive test plan covering five testing domains: Strategy & Scope, UX Validation, Automation & Performance Engineering, AI & Data Specialist validation, and Backend Security. Defined exit criteria including Dice Score ≥ 0.90, zero PII leakage, and API response times under 800ms.
Test Plan Playwright Automation k6 Load Testing WCAG Compliance
February 2026
Demo Presentation & User Surveys
Conducted the Winter 2026 demo presentation showcasing the working prototype. Ran two validation surveys — a Telemedicine Platform Validation Survey and a Patient Trust in Advanced Medical Technology survey for non-medical students — to gather stakeholder feedback.
Live Demo User Surveys Stakeholder Feedback
March 2026
Dubai AI Week — Selected by Dubai Medical University
Dubai Medical University selected Xpert to be showcased at Dubai AI Week, presenting our project and research at DMU's official booth. This recognition positioned Xpert alongside industry-level AI healthcare initiatives and provided direct exposure to medical professionals, researchers, and AI practitioners.
Dubai AI Week DMU Selection Industry Exposure Live Showcase
April 2026
IEEE Research Paper — Accepted for Publication
Under the guidance of Dr. Milan, the team authored a full research paper on Xpert's dual-engine architecture and its application in medical education. The paper was accepted by IEEE for publication and will be presented at the Student Research Conference hosted at Zayed University.
IEEE Publication Research Paper Zayed University SRC Dr. Milan
March – April 2026
Instagram Marketing Campaign — 30K+ Engagement
Launched the official Xpert Instagram account and executed a targeted marketing campaign showcasing the platform's capabilities, team behind-the-scenes, and milestone highlights. The campaign surpassed 30,000 total engagements, building community awareness and validating interest in AI-driven medical education tools.
30K+ Engagement Instagram Campaign Social Media Brand Awareness
March – April 2026
Final Refinement & Project Website
Final round of bug fixes, performance optimization, and documentation polish. Created the project informational website you're viewing now. Preparing for final capstone submission and demonstration.
Final Submission Project Website Documentation
Looking Ahead

Future Expansion

Cloud Deployment

Migrating from SQLite to MySQL with Azure Blob/AWS S3 for DICOM storage, and deploying the FastAPI backend to Vercel or Railway for 24/7 access across medical institutions.

Multi-Pathology Detection

Expanding beyond pneumonia to detect cardiomegaly, pleural effusion, and tuberculosis through an ensemble of specialized vision models.

Dynamic RAG Expansion

Automating ingestion of real-time medical journals and textbooks into the ChromaDB vector database to keep the educational assistant aligned with the latest clinical guidelines.