## Grand X-Ray Slam: Division B
A Kaggle Community Hackathon - Build AI for Life-Saving Radiology

### Overview
Welcome to Grand X-Ray Slam: Division B, the second of a 2-part Kaggle hackathon series where data scientists and AI enthusiasts compete to advance medical imaging. In this challenge, you’ll develop AI models to detect 14 thoracic conditions from chest X-rays, tackling real-world clinical complexity. Your work will power Dr HealthAgent by Blue and Gold Healthcare Inc., enhancing global healthcare.

Top performers across both Division B and Division A will also shine on the Grand Slam Leaderboard, sharing an additional $2,500 prize pool.

### Your Mission
Build AI models to identify the following conditions in each X-ray:

- Atelectasis  
- Cardiomegaly  
- Consolidation  
- Edema  
- Enlarged Cardiomediastinum  
- Fracture  
- Lung Lesion  
- Lung Opacity  
- No Finding  
- Pleural Effusion  
- Pleural Other  
- Pneumonia  
- Pneumothorax  
- Support Devices  

This is **multi-label classification**, reflecting real emergency-room diagnostics.

### Dataset
Train set: 108,494 images (~139 GB)  
Test set: 47,927 images (~60 GB)  
- Images are de-identified chest X-rays from multiple institutions.

### Timeline
- Start: August 20, 2025  
- End: October 15, 2025, 11:59 PM UTC  
- Private Leaderboard Release: October 17, 2025, 23:59 UTC  

### Participation Rules
- Teams: Solo or up to 4 members  
- External data: Not allowed  
- Use: Competition & research only  

### Acknowledgements
**Organizers:**  
- Guntas Dhanjal (Lead)  
- Salah Sammari  
- Fathi Ben Amor  
- Mariem Aissa  

**Data Sources:** Multiple publicly available chest X-ray datasets, fully anonymized and preprocessed to ensure no patient overlap between train and test sets