Artificial Intelligence in Medicine
INTRODUCTORY COURSE
2021
Welcome to our introductory course in medical AI. Originally delivered live in 2021. It is divided into streams to help focus your learning depending on your prior experience and interest.
Introduction to Artificial Intelligence in Medicine
Designed for those in medicine who are interested in learning more about how Artificial Intelligence can be used in their field
Introduction to Medicine
and Medical Data
Designed for those in Computing Sciences interested in how Artificial Intelligence can be applied to the field of Medicine
Learn to use Artificial Intelligence
Designed for beginners who have some coding experience but have never used Python's Keras Library before
Introduction to AI in Medicine
Introducing the concept of artificial intelligence and its role in medicine.
Lecture A1: Intro to AI and Neural Networks
Learn the basics of AI and Neural Networks. What are they and how do they work?
Lecture A2: Working with Data
Learn how data is used when working with AI models in the context of medicine.
Lecture A3: Assessing Performance
Learn how to assess performance of a machine learning model.
Lecture A4: Advanced Architectures
Learn about some of the more advanced architectures used in machine learning.
Lecture A5: Medical Data Types
Learn about common types of medical data.
Lecture B1: Flow of Information in Patient Care
Learn how information and data are collected along patient's journey through the medical system.
Lecture B2: Domains of Medicine & Data Types 1
Learn about health data and AI in family medicine, primary care, and public health.
Lecture B3: Domains of Medicine & Data Types 2
Learn about Internal Medicine, Pharmacy, Surgery, Pathology, Radiology and the types of data they generate.
Lecture B4: Domains of Medicine & Data Types 3
Learn about Psychiatry, Precision Health, Genetics, and the types of data they generate.
Lecture B5: AI in Healthcare Logistics
Learn about the importance of logistics in healthcare and how AI can help.
Closing Lecture: Explainability, Privacy, Ethics, and the Future of AI
Learn about explainability, privacy, ethics, and the future of AI in medicine.
Workshop 1: Intro to coding in Python
In this workshop we introduce the basics of coding in Python
Workshop 2: Introduction to Cloud Computing with Google Colab
Learn how to utilize cloud computing in Google Colab for machine learning.
Workshop 3: Introduction to Keras
Learn how to build an AI model using Keras
Workshop 4: Data Pre-Processing in Python
Learn how to properly prepare your data before using it to train an AI model.
Workshop 5: Optimizing your AI model
Discover the key techniques and strategies to enhance the performance and efficiency of your AI models. Learn how to fine-tune hyperparameters, select appropriate optimization algorithms, and implement regularization techniques.
Workshop 6: Detecting COVID19 Pneumonia with AI
Combine all the skills from the previous workshops to build an AI model that can diagnose COVID pneumonia from X-ray images.
Workshop 7: How to Evaluate a Medical AI Study
Learn how to read, interpret and critique a medical AI study.