This unit introduces core concepts of artificial intelligence, the historical and technical drivers behind its recent rise, and common AI processes used in health informatics. Through executive-summary practice, communication exercises, and case studies (including industry and disaster response examples), learners will build foundational knowledge and readiness for applied, technical, and ethical units that follow.
Learning Objectives
- Analyze foundational artificial intelligence concepts and the historical/technological factors (‘why now’) that enable AI adoption in healthcare, citing specific examples
- Apply common AI processes to design a basic health informatics data-to-insight workflow, specifying data sources, preprocessing steps, model selection rationale, and evaluation metrics
- Demonstrate the ability to create concise executive summaries and stakeholder communications that explain AI project goals, potential benefits, limitations, and ethical considerations for healthcare audiences
- Evaluate real-world AI use cases (such as industry innovations and disaster-response tools) for their potential impact, limitations, and implications for healthcare delivery and emergency response
Curriculum
- 1 Section
- 10 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 1 — Foundations of AI for Health10
- 1.1What Is Artificial Intelligence?20 mins
- 1.2Why Now?20 mins
- 1.3Common Processes20 mins
- 1.4Executive Summary20 mins
- 1.5Executive Summary20 mins
- 1.6Executive Summary20 mins
- 1.7Communication20 mins
- 1.8Amazing Things in the Amazon20 mins
- 1.9Quick Help Saving Lives in Disaster Response20 mins
- 1.10Endnotes20 mins
Instructor
Free
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