Algorithmic Thinking with AI for Data-Driven Medicine

3 credits · Graduate

This lecture course introduces students to algorithmic thinking and the practical use of artificial intelligence, especially large language models (LLMs), in biomedical and clinical research. Students will learn to structure complex medical research questions into algorithmic workflows, deploy AI tools responsibly for literature review, data interpretation, statistical design, and ethical research practices, and communicate findings clearly through visualization and scientific writing. Topics include AI foundations, ethics and bias in medical AI, statistical reasoning with health data, algorithmic research pipelines, visualization techniques, and reproducibility in AI-augmented research. Through interactive labs and a project-based approach, students will develop the ability to design and critically evaluate data-driven medical research using AI.