---
license: mit
---
# LungsAI - Pneumonia Detection Model

## Model Description
LungsAI is a deep learning image classification model designed to analyze chest X-ray images and predict the presence of pneumonia. This AI-powered tool was developed to assist in fast and efficient medical image analysis.

- **Developed by:** Md Shahed Rahman
- **Model type:** Deep Learning Image Classification
- **Application:** Also deployed as a web application using Streamlit
- **License:** MIT

## Model Details
The model weights are saved in the `.h5` format (`pneumonia_model.h5`), making it fully compatible with the Keras and TensorFlow frameworks.

## How to Get Started with the Model
You can easily load and run predictions using this model in Python. Here is a basic code snippet to get you started:

```python
import tensorflow as tf
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing import image
import numpy as np

# 1. Load the model
model = load_model('pneumonia_model.h5')

# 2. Define a prediction function
def predict_pneumonia(img_path):
    # Note: Adjust the target_size based on how your model was trained (e.g., 150x150 or 224x224)
    img = image.load_img(img_path, target_size=(224, 224)) 
    img_array = image.img_to_array(img)
    img_array = np.expand_dims(img_array, axis=0) / 255.0
    
    # Get the prediction
    prediction = model.predict(img_array)
    return prediction

# 3. Test with an image
# result = predict_pneumonia('path_to_your_xray_image.jpg')
# print(result)

Intended Uses & Limitations

    Intended Use: This model is built for educational, research, and portfolio purposes to demonstrate the power of deep learning in healthcare.

    Limitations: This AI model is not a substitute for professional medical diagnosis. It should not be used for real-world clinical decision-making without the supervision of a certified doctor or radiologist.