College Description of AI in Medical Imaging
This course introduces AI in imaging with expanded emphasis on machine learning, pattern recognition, and workflow automation. Students learn how AI tools support diagnostic interpretation and clinical efficiency. Additionally, the course strengthens analytical reasoning and prepares students for advanced informatics roles.
Course Objectives of AI in Medical Imaging
Students will learn to analyze AI algorithms, interpret machine learning outputs, evaluate workflow automation strategies, and apply AI tools to imaging systems. They will also strengthen analytical reasoning, technical interpretation, and informatics proficiency.
Key Topics Covered During AI in Medical Imaging
Machine learning, pattern recognition, workflow automation, AI algorithms, and imaging informatics. These topics provide the foundation for understanding AI in imaging and support advanced clinical applications.
Student Assessment During AI in Medical Imaging
Assessment includes exams, algorithm analysis tasks, workflow evaluations, and AI interpretation assignments. Students will also complete activities that reinforce AI concepts and strengthen technical reasoning.
Average College Credits for AI in Medical Imaging
3
Prerequisites For AI in Medical Imaging
PACS and Imaging Informatics
What Department Teaches AI in Medical Imaging
Imaging Informatics
Who Teaches AI in Medical Imaging
Informatics faculty.