🧬 Breast Cancer Predictor | AI-Powered Diagnosis

📖 Introduction

Breast Cancer Predictor is a Machine Learning-based web application that classifies breast tumors as benign or malignant using cell nuclei measurements. Built with Python, Streamlit, and Scikit-Learn, it provides real-time predictions and an interactive radar chart for visualization.

🚨 Disclaimer: This tool is for educational purposes only and should not be used for medical diagnosis.

🚀 Features

✔️ AI-Powered Classification – Uses a trained logistic regression model.
✔️ Real-Time Predictions – Adjust cell measurements and get instant results.
✔️ Interactive Radar Chart – Compare tumor features visually.
✔️ Streamlit Web Interface – Easy-to-use and interactive UI.
✔️ Local Execution – No external API calls, ensuring data privacy.

🏗️ Technologies

• 🐍 Python 3.12 – Core programming language
• 🎨 Streamlit – Web interface
• 📊 Plotly – Data visualization
• 🤖 Scikit-Learn – Machine Learning model
• 🏥 Breast Cancer Wisconsin Dataset – Training data
• 🛠 Pandas & NumPy – Data manipulation

📦 Installation

1️⃣ Clone the Repository

git clone https://github.com/Yacine-Mekideche/breast-cancer-predictor.git
cd breast-cancer-predictor

2️⃣ Create a Virtual Environment

Using Conda:

conda create -n breast-cancer-predictor python=3.12
conda activate breast-cancer-predictor

Or using venv:

python -m venv venv
source venv/bin/activate  # Mac/Linux
venv\Scripts\activate  # Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

🛠️ Usage : Run the Application

streamlit run app/main.py

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🎯 Demo

📬 Contact Me

💡 Let’s connect! Whether you’re interested in AI, Machine Learning, or tech collaborations, feel free to reach out.

📩 Email for business inquiries: contact@iacine.tech

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