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https://github.com/nurulashraf/ann-cancer-prediction

An Artificial Neural Network built with TensorFlow and Keras to predict breast cancer based on the Wisconsin Breast Cancer dataset.
https://github.com/nurulashraf/ann-cancer-prediction

artificial-neural-network breast-cancer-prediction deep-learning keras machine-learning python scikit-learn tensorflow

Last synced: 20 days ago
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An Artificial Neural Network built with TensorFlow and Keras to predict breast cancer based on the Wisconsin Breast Cancer dataset.

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# Breast Cancer Prediction using Artificial Neural Networks

A simple Artificial Neural Network (ANN) model to predict the presence of cancer using supervised machine learning. This project demonstrates data preprocessing, ANN model creation using TensorFlow/Keras, training, evaluation, and prediction based on a medical dataset.

---

## Features

- Clean and easy-to-understand ANN architecture
- Data preprocessing with scaling and splitting
- Model training with real cancer dataset
- Evaluation using accuracy metrics
- Predictive capability using new patient data
- Jupyter Notebook for interactive learning

---

## Project Structure

- **`data/`**: Contains the dataset used for analysis and prediction.
- **`notebooks/`**: Jupyter notebooks for data analysis, feature engineering, and model building.
- **`requirements.txt`**: List of required Python packages
- **`LICENSE`**: MIT License file
- **`README.md`**: Project overview and usage instructions.

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## Tools & Libraries

- Python 3.x
- TensorFlow
- Keras
- NumPy
- Pandas
- scikit-learn
- Matplotlib

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## How to Use

### 1. Clone the repository

```bash
git clone https://github.com/nurulashraf/ann-cancer-prediction.git
cd ann-cancer-prediction
````

### 2. Install required libraries

It is recommended to use a virtual environment.

```bash
pip install -r requirements.txt
```

### 3. Run the notebook

Open the Jupyter Notebook:

```bash
jupyter notebook ann_cancer_prediction.ipynb
```

Follow the steps in the notebook:

* Load and explore the data
* Preprocess the data
* Define and train the ANN model
* Evaluate model accuracy
* Make predictions with new input data

---

## License

This project is licensed under the MIT License.
See the [LICENSE](https://opensource.org/licenses/MIT) file for details.