SYSEN 5640

AI for Healthcare System Engineering

Course Description

Course information provided by the 2026-2027 Catalog.

The purpose of this class is to teach students the fundamentals of artificial intelligence (AI) technologies and how they can be applied in various healthcare system engineering problems. We will introduce conventional AI technologies including supervised learning for tasks like clinical risk prediction and computer assisted diagnosis, unsupervised learning methods for subtype identification and pattern discovery; as well as deep learning methods, including the basic perceptron and feedforward neural networks for standard vectorized data, convolutional neural networks for analyzing medical images, recurrent neural networks and transformer for analyzing event sequences and temporal signals, and graph neural networks for analyzing networks and relational data. The class includes both lectures introducing algorithms and theories, and programming exercises to get hands-on experience on implementing these algorithms with Python.

Last 4 Terms Offered 2026SP, 2025SP

Learning Outcomes

• Analyze health system engineering problems and their typical setups.
• Identify and implement appropriate machine learning algorithms for solving different health system engineering problems.
• Analyze the results of machine learning solutions and demonstrate their effectiveness.

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