I'm a Final Year CS student specialising in Data Science and AI with hands-on experience in Python, machine learning, deep learning and data analytics. I enjoy turning raw data into practical, actionable insights that solve real-world problems.
Programming:
Data Analysis & Science:
Machine Learning & AI:
Tools & Platforms:
Deployment:
Visual Analytics Dashboard for Patient Pathway & Hospital Flow Management
Capstone Project | Taylor's University, Malaysia
MediVision is a full-stack hospital emergency department patient flow management system built to streamline hospital pathway, triage and clinical decision-making in real time built by a team of 5 members for our final year project (Capstone Project).
- 🧑⚕️ Patient Registration & Tracking - Vital signs, chief complaint & auto ID generation
- 📊 Admin Dashboard - Real-time stats, triage pie charts & patient status management
- 👨⚕️ Clinician Dashboard - Live waiting queue, treatment assignment & AI triage recommendation
- 🔐 JWT Authentication - Role-based access for Admin & Clinician
| Level | Colour | Priority | Response Time |
|---|---|---|---|
| Category 1 | 🔴 Red | Critical | Immediate |
| Category 2 | 🟡 Yellow | Urgent, but stable | 30 mins |
| Category 3 | 🟢 Green | Non-urgent | 60 mins |
| Position | Competition | Event | Year |
|---|---|---|---|
| 🥈 Finalist | UG Research Idea Pitch Competition - Centre for Active Living (CAL) | Research & Innovation Festival 2025, Taylor's University, Malaysia | 2025 |
| Project | Description | Output |
|---|---|---|
| 🌿 Smart Monitoring for Houseplants | IoT prototype using ESP32 & Raspberry Pi for automated plant watering and monitoring of moisture, temperature, humidity and pH | Circuit Simulation |
| 🎬 Sentiment Analysis on IMDB Reviews | Bidirectional LSTM model trained on IMDB movie reviews for binary sentiment classification | 86.8% accuracy |
| 🧠 Mental Health Sentiment Analysis | Text classification on 53K+ mental health statements using Decision Tree and Neural Network | 93.58% accuracy |
| 💳 Predicting Loan Defaults | ML models (kNN & Decision Tree) to analyse loan default risk on a financial dataset | 88.54% accuracy |
| 🦴 Bone Fracture Detection | CNN model to automatically detect bone fractures in X-ray images using Computer Vision | 73.84% accuracy |
| ❤️ Heart Disease Prediction | Logistic Regression model with EDA on the UCI Heart Disease dataset to predict risk | 66.67% accuracy |
| 💊 Analyse Lethal Drug Combinations | Data mining on drug-death records using Random Forest, K-Means clustering and Isolation Forest | 81% accuracy |