Amir-Hofo/Pneumonia_Classifier_Using_Chest_XRay
In this notebook, we perform a binary classification on chest X-ray images to determine whether a person has healthy lungs or is diagnosed with pneumonia. For this classification, we used a custom deep convolutional neural network (CNN) model and achieved an accuracy of 95% on the test set.
This tool helps medical professionals quickly assess chest X-ray images to determine if a patient has pneumonia or healthy lungs. By inputting a patient's chest X-ray, it outputs a classification indicating the presence or absence of pneumonia. Radiologists, general practitioners, and emergency room physicians can use this to aid in initial diagnostic screening.
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Use this if you need an automated initial screening tool to quickly classify chest X-ray images for potential pneumonia.
Not ideal if you require a multi-class diagnosis distinguishing between specific types of lung conditions or viral vs. bacterial pneumonia.
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Apr 02, 2025
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