Machine Learning Fundamentals for Healthcare

Introduction

• Understanding machine learning in healthcare
• What you should know

1. Fundamentals of Machine Learning for Healthcare

• Machine learning, artificial intelligence, and data science
• Applications of machine learning in healthcare
• How to think about machine learning in healthcare
• Machine learning vs. rule-based programming in healthcare
• Types of machine learning in healthcare
• Healthcare data types for machine learning
• Features and labels in machine learning for healthcare
• Machine learning models and algorithms in healthcare
• Deep learning models and architecture in healthcare
• Transfer learning and pretrained models in healthcare
• Assessment metrics for machine learning models
• Tools and libraries for machine learning
• Data privacy and ethics in healthcare machine learning
• Career opportunities in machine learning for healthcare

2. Machine Learning for Tabular Healthcare Data

• How to use a Google Colab Notebook
• Explore the heart failure clinical record dataset
• Classification task: Heart failure outcomes prediction with no feature scaling
• Classification task: Heart failure outcomes prediction with feature scaling
• Regression task: Predict the heart rejection fraction
• Feature importance in regression tasks

3. Machine Learning for Tabular Healthcare Data: Unsupervised

• Clustering task: Localization data for person activity
• Dimensionality reduction: Localization data for person activity

Conclusion

• Next steps