How Artificial Intelligence Can Support Healthcare
Explore how AI can be used to improve patient care and build your understanding of how to implement AI in the health professions.
Practical information:
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Understand real-life AI healthcare applications and their impact on healthcare
The use of artificial intelligence to improve efficiency is prevalent across almost every industry, none more so than the world of healthcare.
On this course, you’ll learn how to join the discussion on the potential of AI in healthcare in a useful and realistic way.
With the help of teachings from leaders in AI healthcare thinking, you’ll build your knowledge and confidence in key areas of AI healthcare, before learning how it can be implemented into your own workflow.
Understand the key challenges of AI in healthcare, including AI ethics
Whilst AI is undoubtedly creating many opportunities to improve healthcare provision, it also brings risks and challenges.
From social to ethical, using real-life examples you’ll explore what these risks are so that you can make an informed decision about using AI in your line of work.
The final steps of the course will show you how to introduce AI into your workflow in a meaningful, safe, legal, and ethical way to benefit your patient.
Explore the potential of artificial intelligence in healthcare
There is a wide range of healthcare-based use-cases for AI, including in the automation of repeated tasks and in improving the accuracy of diagnosis. This course will take you through the full range of AI capabilities and why they are so useful.
You’ll also learn what the requirements are for implementing AI in a clinical environment and what the impact of that implementation is.
Study with AI healthcare experts from across Europe
This course is led by a partnership of universities, consisting of University Medical Center Groningen, University of Tartu, University of Copenhagen, University Medical Center Cologne, and several industry partners.
Teachers / speakers
Associate Professor Imaging Informatics at dept. of Radiotherapy and coordinator of the Machine Learning Lab of DASH both at the University Medical Center Groningen.
Data Science & AI educator and biomedical data scientist.
Assistant Professor of Health Informatics at the Institute of Computer Science, University of Tartu
MSc Artificial Intelligence and Human-Machine Communication. Content developer AIProHealth at the Data Science Center in Health of the University Medical Center Groningen.
I am an Assistant Professor of Radiology at the University Hospital of Cologne. In my research I focus on the advancement of data driven approaches in radiology - from structured reporting to AI.
Biomedical engineer, PhD in aging, and postdoc at University of Copenhagen. Co-founder and CEO of Tracked.bio.
