This project explores ischemic heart disease trends in Nigeria using data visualizations and machine learning to uncover insights into mortality, healthcare access, and spending.
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# 🫀 Ischemic Heart Disease Analysis & Dashboard – Nigeria
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## 📊 Overview
This project presents a **comprehensive data-driven analysis** of **Ischemic Heart Disease (IHD)** in Nigeria, focusing on trends, demographics, healthcare infrastructure, and expenditure.
It includes:
* A **Streamlit-powered interactive dashboard** for real-time exploration 📈
* A **classification model** to predict heart disease risk using machine learning 🔍
> Built with Python, Pandas, Plotly, and scikit-learn.
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## 🚀 Features
### 📉 Exploratory Data Analysis
* 📆 **Yearly Trends** in IHD deaths (by gender & age group)
* ⚰️ **Top Causes of Death** comparison to IHD
* 🏥 **Doctor-to-Patient Ratio** tracking over time
* 💰 **Health Expenditure per Capita** visualization
### 🧠 Classification Modeling
* Logistic Regression, Random Forest, and Decision Tree models evaluated
* Key metrics: **Accuracy, Precision, Recall, F1 Score, Log Loss**
* Decision Tree emerged as the best performer with **\~82% accuracy**
### 🖥️ Interactive Dashboard (Streamlit)
* Real-time bar, pie, and line charts
* Responsive layout for seamless exploration
* Clean, minimal design with actionable insights
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## 🖼️ Dashboard Preview
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## 🗂️ Project Structure
```
Ischemic-heart-disease-/
├── analysis/
│ ├── dashboard.py # Streamlit app source
│ ├── IHD_analysis.ipynb # Jupyter notebook (EDA + ML models)
│ ├── cleaned_data/ # Cleaned datasets
│ └── rough_data/ # Raw or semi-clean datasets
│ └── IHD_dashboard.jpeg
├── requirements.txt # Project dependencies
├── README.md # This file
└── LICENSE
```
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## ⚙️ Getting Started
### ✅ Prerequisites
* Python 3.8+
* pip (Python package manager)
### 💻 Installation
```bash
git clone
github.com
cd Ischemic-heart-disease-
pip install -r requirements.txt
```
### 🚀 Run the Dashboard
```bash
streamlit run /analysis/dash …