ISM1216131 - Artificial Intelligence for
Medicine II
Spring 2025
Course Info:
This course provides an in-depth exploration of the applications, challenges, and future directions of Artificial Intelligence (AI) in the field of medicine. Students will learn the fundamentals of AI, machine learning, and data science, and how these technologies are transforming healthcare, from diagnostics to treatment planning and patient care. Students will learn about various AI techniques and their implemention in medical practice and in their medical education. The course will provide applications that will include AI in diagnosticis, treatment, patient care, and image/data analysis. The course combines theoretical concepts with practical case studies and hands-on exercises/projects.
Prerequisite Courses
Artifical Intelliigence for Medicine I
Required Text(s)
| There are no required textbooks for this course. Reference and reading materials will be provided via the course web site and/or Microsoft Teams. |
Recomended Text(s)
Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud, Paul Deitel, Harvey Deitel, Pearson, 2020 (html).
-
https://libguides.pcom.edu/ai_medicine/ebooks
- LLMs
and Generative AI for Healthcare by Kerrie
Holley, Manish
Mathur Released August 2024 Publisher(s): O'Reilly Media, Inc.
-
https://www.pythonhealthdatascience.com/content/front_page.html
Meeting Times:
- Thursday 13:30 - 15:20, Location: 1001 - South CampusLabs:
- Lab : No labsTentative Grading:
| Evaluation Tool | Weight in % |
|---|---|
| Assignments | 15 |
| Group Project | 15 |
| Presentations | 5 |
| In-term Exams - Midterm |
25 |
| Final | 40 |
Tentative Course Outline:
| WEEK | TOPIC(S) |
|---|---|
| 1 | Introduction to AI Methods and their Applications in Medicine |
| 2 | Machine Learning Basics |
| 3 | Data Collection and Preprocessing |
| 4 | Supervised Learning |
| 5 | Unsupervised Learning |
| 6 | Model Evaluation and Performance Metrics |
| 7 | Deep Learning in Medicine |
| 8 | Medical Imaging and AI |
| 9 | Natural Language Processing (NLP) in Healthcare |
| 10 | AI in Diagnostics and Disease Prediction |
| 11 | AI in Personalized Medicine, Treatment Planning, Drug Discovery |
| 12 | AI in Medical Robotics and Genomics |
| 13 | Challenges and Limitations of AI in Medicine, and Future Trends |
| 14 | Course Review |
| 15 | Presentations |