Applications of AI in Healthcare

1 Unit · Graduate

This course provides a practical, interdisciplinary exploration of applied artificial intelligence (AI) in healthcare, with a focus on high-impact use cases using traditional AI, Natural Language Processing (NLP), and generative AI to demonstrate pragmatic applications of AI across the healthcare ecosystem. Students will examine real-world implementations ranging from automated clinical documentation and radiology image analysis to predictive risk modeling and AI-assisted care delivery. Designed for healthcare and analytics professionals, this course emphasizes how to evaluate, implement, and lead AI-driven solutions, rather than build them from scratch. Through hands-on case studies and interactive scenario planning, students will learn how to assess data readiness, address model limitations, and communicate the value of AI tools to clinical and operational stakeholders. Key topics include AI adoption frameworks, handling messy healthcare data, evaluating vendor tools, understanding ethical and regulatory considerations (e.g., HIPAA, bias mitigation, FDA guidance), and aligning AI innovation with organizational goals. By the end of the course, students will be equipped to bridge the gap between advanced AI technologies and responsible, outcome-driven implementation in healthcare settings.