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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.

3,003 enrolled on this course

Medical researcher with futuristic display

How Artificial Intelligence Can Support Healthcare

3,003 enrolled on this course

  • 4 weeks

  • 4 hours per week

  • Digital certificate when eligible

  • Intermediate level

Find out more about how to join this course

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.

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.

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.

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.

Estonian e-course quality label Awarded e-course of the year 2023
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Skip to 0 minutes and 4 seconds Within healthcare and biomedical research, artificial intelligence, or AI, holds the promise of automation of tasks to deliver faster diagnoses and provide better care. However, among healthcare professionals and the general public, knowledge on the latest developments and skills in AI are still very limited. This causes anxiety, which leads to potentially unrealistic expectations, in turn drastically decreasing the speed of adoption of AI in healthcare. For patient care to benefit from AI we need to decrease anxiety and increase knowledge for everyone involved in healthcare. Physicians, managers, researchers, nurses, technicians, AI developers, patients, and the general public.

Skip to 0 minutes and 55 seconds We will prepare you for the inevitable change that AI will bring to healthcare. This course will not only demonstrate the vast possibilities of AI application, but also introduce some of the legal, technical, and ethical boundaries. During the course, you will be hearing from people with varying backgrounds about their consideration towards AI and how they currently apply AI in healthcare. After completing this course, you will have a clear and realistic view of the use and the usefulness of AI in healthcare. You will be able to identify the requirements of the implementation of AI in a clinical environment, describe what impact this would have, and evaluate the challenges and risks of AI in healthcare.

Skip to 1 minute and 40 seconds This course was designed by an international group of experts to ensure that anyone, at any level of expertise, will be able to participate. Join this course to deliver faster diagnoses, and provide better care through AI.


  • Week 1

    Potential and limitations of AI in healthcare

    • Introduction to the course

      This activity introduces the course How Artificial Intelligence Can Support Healthcare. The course outline and learning objectives are described and the educators are introduced.

    • What is artificial intelligence?

      In this activity, learners will see examples of AI in real life, learn how it works, and practice to distinguish AI from non-AI systems.

    • Technical background of AI

      The previous activity has introduced the basics behind artificial intelligence. This activity explains the technical background in more detail.

    • Opportunities for AI in healthcare

      Case reports and examples of how artificial intelligence can be used in healthcare.

    • Limitations of AI

      Previously, the potential of AI in healthcare has been discussed. This activity covers the limitations that need to be considered before implementation.

    • Concluding Week 1

      A review of this week’s materials and a final test to check comprehension.

  • Week 2

    Tackling the technical and regulatory challenges of AI

    • Introduction Week 2

      Introduction of this week, where you encounter technical and regulatory challenges of artificial intelligence, in particular in the field of healthcare.

    • Trustworthy AI

      This activity describes the Ethics Guidelines for Trustworthy AI. One requirement for trustworthy AI, bias, is explained in more detail with the use of examples.

    • Explainable AI

      This activity covers the topic of explainable AI, a subfield of AI which helps users to understand the system better.

    • Clinical Products and Services using AI

      For AI to be used in healthcare, the system must adhere to the General Data Protection Regulation (GDPR), Medical Device Regulation (MDR) and In Vitro Diagnostics Regulation (IVDR).

    • Concluding Week 2

      A review of this week’s materials and a final test to check comprehension.

  • Week 3

    Ethical and social aspects of AI in healthcare

    • Introduction Week 3

      Ethical and social issues in AI in healthcare.

    • Ethical concerns

      Discussion of the ethical issues of AI in healthcare. Examples from the news are displayed and patients share their concerns. Learners are asked to think along.

    • Dealing with ethical concerns

      Healthcare professionals explaining how they deal with ethical concerns of their patients. Ethics experts responding to ethics concerns raised by patients. How to use AI responsibly?

    • Interaction between AI and healthcare professionals

      Highlighting the artificial intelligence-healthcare professional interaction. Explanation of deskilling and over-reliance and preventing those.

    • Patients interacting with AI

      We show ways in which patients can directly interact with AI. How does this relate to ethical issues?

    • Can we trust AI?

      Urging the learners to think about the trustworthiness of AI by showing a debate between critics.

    • Future perspectives

      Healthcare professionals discuss the future role of artificial intelligence in healthcare as well as whether AI will replace the healthcare professional.

    • Concluding Week 3

      A recap of this week’s materials and a final test to check comprehension.

  • Week 4

    Practical examples and wrap-up

    • Introduction Week 4

      Introduction of this week. Explanation of the planning. Getting to know the storyline of this week.

    • Manager’s perspective

      Meet our manager, Lisa who wants to use an AI application in the clinical center she works for. How can she assess the potential AI solutions?

    • IT perspective

      In this activity, the requirements are discussed from an IT perspective.

    • Healthcare professional perspective

      In this activity Lisa will investigate AI solutions from the healthcare professional’s perspective.

    • Patient perspective

      In this activity we examine AI solutions from the patient’s perspective.

    • Making a choice

      In this activity Lisa explains the reasoning behind the choice for the best AI solution for her department.

    • Concluding Week 4

      We round up Week 4 and the course.

When would you like to start?

Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Explain the fundamentals of AI and its use in healthcare-based use-cases.
  • Identify the requirements of implementation of AI in a clinical environment.
  • Describe the impact of implementation of AI in a clinical environment.
  • Evaluate the challenges and risks of AI in Healthcare.
  • Discuss about AI and its use in healthcare in a practical and meaningful way.

Who is the course for?

This course is designed for healthcare professionals who want to better understand AI for healthcare.

This includes doctors, nurses, GPs, and Biomedical researchers. It will also be of interest to patients, medical students, PhD students, and general AI enthusiasts.

Who will you learn with?

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.

Who developed the course?

University of Groningen

The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, in the north of the Netherlands.

University of Tartu

The University of Tartu is Estonia’s leading centre of research and training and belongs to the top 1.2% of world’s best universities.

OneVision Healthcare

OneVision Healthcare provides professional services and international networking opportunities for HealthTech organizations and AI solution providers in healthcare.

University Medical Center Groningen (UMCG)

UMCG is building the future of health through its focus on complex patient care, research, education and training.

In collaboration with


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University Hospital Cologne

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Ways to learn

Choose the best way to learn for you!

Buy this course

$134/one-off payment

Fulfill your current learning need

  • Access to this course
  • Learn at your own pace
  • Discuss your learning in comments
  • Tests to boost your learning
  • Printed and digital certificate when you’re eligible

Subscribe & save

$349.99 for one year

Automatically renews

Develop skills to further your career

  • Access to this course
  • Access to 1,000+ courses
  • Learn at your own pace
  • Discuss your learning in comments
  • Tests to boost your learning
  • Digital certificate when you're eligible

Cancel for free anytime

Limited access


Sample the course materials

  • Access expires 12 Aug 2024

Find out more about certificates, Unlimited or buying a course (Upgrades)

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