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This project is done as part of the Machine Learning subject in our curriculum.

Jupyter Notebook 100.00%
cnn cnn-keras pneumonia-classification pneumonia python chest-xray-images pneumonia-detection deeplearning machine-learning tensorflow

pneumonia-detection-using-cnn's Introduction

Pneumonia-detection-using-CNN

Pneumonia infection is a serious disease of the lungs with a range of possible causes. Bacteria, viruses or fungi can cause Pneumonia infection. Pneumonia is ranked as eighth leading for causing more no. of deaths in the US, It causes death in children younger than five years of age worldwide. To save precious lives of many people, humans and technology should interact.


Chest X-rays are used for detecting the Pneumonia infection and to locate the infected area in the lungs. So, To detect the the pneumonia radiologist have to observe the chest xray and he/she has to update the doctor correctly. The main objective of this model is to identify if the person has Pneumonia or not with high accuracy so that the person can get treatment as soon as possible. Deep Learning models which are trained correctly by using good datasets can be helpful for doctors. To train the model for detecting whether the person has pneumonia or not, A Convolutional Neural Network(CNN) is used. The CNN can train the images of chest xrays and then it can predict with high accuracy.


Here you can download the saved model.

You can use the saved model for predicting. Refer the colab notebook.

Dataset used : here.

Dataset with usability 8.8 : here.

All the required libraries, dataset link are also mentioned in the Colab notebook.

πŸ‘‰ Reference

Hope this helpsπŸ™‚.

Thank you..

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