Our goal is to develop a machine learning prediction algorithm for neurological injury in pediatric cardiac patients.
The biggest risk factor for Pediatric EcMo patients is stroke. We have built a framework to statistically assess actionable events leading to stroke and improve neurological outcomes.
- Python 3.6
- Keras
https://github.com/NCBI-Hackathons/EcMOdel.git
Add raw data into '/data' folder.
Run 'main.ipynb' to train/test model.
Final results are saved in '/results' folder.
- Abdelaziz Farhat, MD - UT Southwestern, Children's Medical, Pediatric Critical Care
- Neel Shah, MD - UT Southwestern and Children's Medical, Pediatric Critical Care
- Ziheng Wang, PhD - UT Dallas, Mechanical Engineering
- Jeon Lee, PhD - UT Southwestern, Bioinformatics
- Rafe McBeth, PhD - UT Southwestern, Radiation Oncology