---
language: en
license: mit
library_name: tf
tags:
- chest-xray
- pneumonia
- medical
- tensorflow
- image-classification
datasets:
- chest-xray
---

# Chest X-Ray Pneumonia Detection Model

This model classifies chest X-rays as either normal or showing signs of pneumonia.

## Model Description

This deep learning model was trained on the Chest X-Ray dataset to differentiate between normal lungs and those affected by pneumonia. It uses transfer learning with a pre-trained network to achieve high accuracy.

### Intended Use

This model is for **research and educational purposes only**. It should not be used for clinical diagnosis or medical decision-making without proper clinical validation.

## Usage

```python
import tensorflow as tf
from preprocessing import preprocess_image

# Load the model
model = tf.keras.models.load_model("model.keras")

# Preprocess an image
img = preprocess_image("path/to/chest_xray.jpg")

# Make prediction
prediction = model.predict(img)
probability = prediction[0][0]

# Interpret results
if probability > 0.5:
    result = "PNEUMONIA"
    confidence = probability
else:
    result = "NORMAL"
    confidence = 1 - probability

print(f"Prediction: {result} with {confidence:.2%} confidence")
```

## Limitations

- This model should not be used as a substitute for professional medical diagnosis
- Performance may vary across different patient demographics and equipment
- The model was trained on a specific dataset which may not represent all clinical scenarios