https://github.com/lucianoscarpaci/preneumonia-classification
EfficientNet-Based Deep Learning Model for Early Preneumonia Detection. This project uses Pytorch and EfficientNet to perform classification on X-ray images whether it is Preneumonia or Normal.
https://github.com/lucianoscarpaci/preneumonia-classification
convolutional-neural-networks data-preprocessing deep-learning early-prediction efficientnet image-classification medical-imaging model-training-and-evaluation performance-metrics pytorch transfer-learning x-ray-images
Last synced: 7 months ago
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EfficientNet-Based Deep Learning Model for Early Preneumonia Detection. This project uses Pytorch and EfficientNet to perform classification on X-ray images whether it is Preneumonia or Normal.
- Host: GitHub
- URL: https://github.com/lucianoscarpaci/preneumonia-classification
- Owner: lucianoscarpaci
- License: mit
- Created: 2024-12-29T03:18:30.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-12-29T20:26:03.000Z (9 months ago)
- Last Synced: 2025-01-25T09:13:16.896Z (9 months ago)
- Topics: convolutional-neural-networks, data-preprocessing, deep-learning, early-prediction, efficientnet, image-classification, medical-imaging, model-training-and-evaluation, performance-metrics, pytorch, transfer-learning, x-ray-images
- Language: Jupyter Notebook
- Homepage:
- Size: 2.54 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Preneumonia-Classification
EfficientNet-Based Deep Learning Model for Early Preneumonia Detection
## Overview
This project leverages PyTorch and EfficientNet to classify X-ray images as either Preneumonia or Normal. The model aims to assist in the early detection of preneumonia by analyzing medical imaging data.
## Features
- Utilizes EfficientNet for robust image classification
- Implements PyTorch for model training and evaluation
- Detects the presence of preneumonia with high training accuracy
## Results
While the model demonstrates high training accuracy, it exhibits lower test accuracy. This indicates potential overfitting, but it successfully detects the presence of preneumonia in the training data.
## Installation
To get started, clone the repository and install the required dependencies:
In Docker and JupyterLab
```bash
git clone https://github.com/lucianoscarpaci/Preneumonia-Classification.git
```
## License
This project is licensed under the MIT License.