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AI for Medical Imaging Bootcamp

Introduction

AI is not only for engineers. AI is for everyone, regardless of your formal degree or eventual career goals. However, for someone new to the field of AI, the huge set of tools required to master AI can be quite overwhelming. You need to learn a new programming language, its syntax and the whole set of libraries required to apply AI algorithms to real-life datasets. It is hard to know where to start.

The goal of this bootcamp is to help solve this problem by providing an introduction to the field of applied Artificial Intelligence and iteratively introduce the concepts required to master the field of applied Artificial Intelligence for medical imaging. Note that “applied” AI focuses more on the application of AI techniques to a specific use case, rather than “theoretical” AI, which deals more with the underlying math and theory – the goal of this bootcamp is to prepare students for applying AI in medical imaging (though having conceptual understanding of the theory is important).

By the end of this bootcamp, you will have demonstrated the basic skills to successfully begin working in AI research in medical imaging. The bootcamp consists of a) required readings and b) interactive Google Colab notebooks with self-grading tests. The skills and knowledge presented here are the minimum of what we expect you to demonstrate. If you are already proficient in these skills, the tests will be easily completed. If you are not proficient in these skills, this is an opportunity to self-study and practice based on online materials – note that this is a crucial skill since code and software for AI changes regularly and AI research necessarily requires continual ‘self-study’ of new code repositories.

Coding Modules

  1. Data Science
  2. Image Processing
  3. Conventional machine learning
  4. Deep learning

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