🎓 Teaching

🤖🩺Machine Learning in Healthcare

The module Machine Learning in Healthcare, which explores the application of modern machine learning techniques to real-world healthcare problems. The course covers foundational concepts, practical tools, and ethical considerations in deploying AI in clinical settings.

Topics Covered

• Introduction to Machine Learning
• Data Preprocessing in Healthcare
• Supervised and Unsupervised Learning
• Deep Learning for Medical Imaging
• Natural Language Processing for Clinical Text
• Model Evaluation and Validation
• Ethical and Regulatory Issues in Healthcare AI

Recommended Resources

Books

• Machine Learning Yearning by Andrew Ng (free online book)
• Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol
• Introduction to Machine Learning with Python by Andreas C. Müller & Sarah Guido

Online Courses

• Coursera: AI for Medicine Specialization (by deeplearning.ai)
• edX: Machine Learning for Healthcare (by HarvardX)
• Stanford CS229: Machine Learning

Tutorials & Datasets

• Kaggle: Healthcare Datasets
• Scikit-learn Tutorials
• TensorFlow Tutorials

Papers & Reviews

• A Survey of Machine Learning for Big Code and Naturalness
• Opportunities and obstacles for deep learning in biology and medicine

Feel free to reach out if you have questions or want to discuss project ideas!