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This course provides an introduction to the basic principles, methods, and applications of deep artificial neural networks to scientific data with an emphasis on medical image data. Students will learn how AI can be used in a variety of scientific contexts, from analyzing images for diagnostics or predicting outcomes, to uncovering new insights into biological processes. The course will cover the fundamentals of AI including mathematical tools related to linear algebra, calculus and probability theory as well as discuss practical implementations such as network architectures and optimization algorithms. Furthermore, students will apply these concepts to real-world problems by building their own AI models using software packages like Pytorch. Finally, the course will emphasize ethical considerations when applying AI systems within a healthcare context. This class is designed for both science and medical students looking to gain experience in machine learning techniques geared towards medical image analysis.

Course Numbers

  • Undergraduate
    • Course Number: MAT-4930
    • CRN: 12692
  • Graduate
    • Course Number: MAP-6436
    • CRN: 12691


Email whahn@fau.edu

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  • Englantina Selfo
  • Andrea Facusse
  • Marina Oliynyk

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