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Detecting Pneumonia from X-Ray images

Dataset Description

The dataset used in this notebook (Mooney, 2018) is already organized into 3 folders: train (containing 5216 JPEG images), val (containing 16 JPEG images) and test (containing 624 JPEG images). These chest X-ray images are organised into two subfolders based on the manual assessment from three expert physicians: Normal if the lungs in the image look normal; Pneumonia if the lungs in the image have been diagnosed with pneumonia.

These images have a wide range of resolutions and aspect ratios.

Task Description

The task is to create a binary classifier that is able to read a chest X-ray and determine whether a chest is normal or has pneumonia.

In other words, there are two classes:
0 = Normal
1 = Pneumonia