week 2

We’ll dive into the essentials of machine learning, deep learning, and natural language processing. This foundational knowledge will help you better appreciate how AI is currently revolutionizing medical imaging, electronic health records, and genomics to improve diagnosis and treatment outcomes.

Intended Learning Outcomes

Here are some things you’ll be able to appreciate by the end of the week:

  • Understand the Fundamentals of Machine Learning: You'll learn the difference between labeled and unlabeled data and explore the main types of machine learning: supervised, unsupervised, and reinforcement learning. Understand key supervised learning tasks—regression for predicting continuous outcomes and classification for discrete classes—along with the role of feature selection. Explore deep learning, its principles, neural networks, and foundation models, including Large Language Models (LLMs). Finally, discover a key healthcare application of deep learning: human phenotyping and its various aspects.
  • Identify the Main Applications of AI in Medicine: You'll explore how AI is transforming medicine, particularly in radiology, electronic health records applications, and hematology. Learn how AI enhances radiology by improving patient safety, automating image analysis, and addressing key challenges in medical imaging. Discover its role in electronic health records for prognostication, risk stratification, diagnosis, and therapy planning, including the use of large language models (LLMs) for high-resolution medical data. Finally, examine AI’s impact on genomics and hematology, from next-generation sequencing to personalized leukemia treatments.