Pneumonia Chest X-Ray Classification Challenge

Overview

Early detection of pneumonia can save lives. Pneumonia is a serious lung infection that affects millions worldwide, especially young children and the elderly. Chest X-rays are a common diagnostic tool, but interpreting them requires medical expertise.

In this challenge, your task is to build a deep learning model that can classify whether a chest X-ray image shows signs of pneumonia or not. This challenge simulates a real-world medical AI application and is suitable for intermediate to advanced participants interested in healthcare and computer vision.

Practice Skills

• Python
• Deep learning
• Image processing
• Image classification

Evaluation

Goal

Classify the given images in the dataset as Pneumonia or Normal.

Metric

Models will be evaluated based on Accuracy metric.

• Accuracy = Correct Predictions / Total Predictions

Submission

Submission guide

Your submission file must be a CSV file with the following structure:

id	label
ce6e440e-2cfc-4684-97d7-fa3a7db7d799.jpeg	0
dec0a17f-9981-423e-8e0e-ebee7cb51b23.jpeg	1

• id: The unique name corresponding to each image.
• label: The predicted label for the corresponding image.

The challenge includes two types of submissions

Public Submission

• Use the public testing dataset (provided in the Data section) to predict your submission file.

Private Submission

• Evaluated on a hidden private testing dataset.
• The private testing dataset contains the same file types as the public testing dataset.
• Important: you must recursively scan the entire data directory (Code section for details).