Holistic AI in Medicine
Learn how AI combines different types of medical data—scans, notes, lab results, and more—to improve how patients are diagnosed, cared for, and treated.
Course Information
Certificate Track
About this Course
Discover how artificial intelligence (AI) is changing medicine by bringing together data from across a patient's care journey. In this course, you'll explore the Holistic AI in Medicine (HAIM) framework—an approach that combines multiple types of health data, like medical images, doctor's notes, lab results, and heart monitor readings, to build smarter, more complete AI systems for healthcare.
Through 12 case studies developed with MIT and Hartford HealthCare, you'll see how AI is being used across cardiology, psychiatry, surgery, trauma care, and more. You'll learn how to clean and organize complex medical data, build models that predict risk and guide treatment, and interpret what those models are actually telling you—so clinicians can trust and act on the results.
Holistic AI in Medicine is one of the industry-specific courses in Universal AI, a self-paced program designed to help you go from beginner to AI authority—no coding or technical skills required.
What you'll learn
- Understand how different types of medical data—including images, waveforms, text, and lab results—are combined to build more powerful AI systems
- Walk through real AI pipelines used in clinical settings, from early disease detection to treatment recommendations and hospital operations
- Learn how to interpret what an AI model is doing and why, using tools like feature importance scores and decision trees
- Recognize common pitfalls in healthcare data—like bias and data quality issues—and learn practical methods for addressing them
- Evaluate AI model performance using metrics that are meaningful in a clinical context, not just in a technical one
- Appreciate why interpretability, ethics, and collaboration with clinicians are essential to building AI tools that can actually be trusted and deployed
Meet your instructors
Georgios Margaritis
PhD candidates in Operations Research at MIT
