AI Adoption in Healthcare: Moving from Fear to Fearless
What to expect?
Join Mozzi Etemadi, Director of Advanced Technologies at Northwestern Medicine, Kristjana Ósk Kristinsdóttir, ML Engineer at Northwestern Medicine, and Thomas Capelle, Machine Learning Engineer at W&B, as they explore the journey of building machine learning models with clinical data and the role Weights & Biases plays in creating an end-to-end ML workflow.
In the session, you will learn:
The rise of transformer models in healthcare
• Fitting your data into models not specifically designed for it.
• Quickly accessing and modifying HuggingFace models.
How to view and configure enterprise-grade healthcare data in W&B
• Loading and viewing SQL data and working with it directly in PyTorch datasets and wandb tables.
• Loading and viewing DICOM data, and working with it in wandb tables and reports.
The key metrics to measure model performance for medical applications
• Ensuring a full-efficiency training setup.
• Making sure your model is actually converging, and troubleshooting when it's not.