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AI for Healthcare: Equipping the Workforce for Digital Transformation

Learn how artificial intelligence is transforming healthcare and how it can be used to support change in the healthcare workforce.

6,561 enrolled on this course

AI for Healthcare: Equipping the Workforce for Digital Transformation

Build your digital understanding and become a champion for AI in healthcare

AI is transforming healthcare in a variety of beneficial ways, from streamlining workflow processes to making more precise patient diagnoses. However, this is not without its challenges.

The University of Manchester has partnered with Health Education England to create a course for you to see real-world examples of how AI is transforming areas such as radiology, pathology, and nursing.

On this course, you will develop your own digital skills and increase your understanding of technology for healthcare, so that you can join the conversation on embedding AI in healthcare practice.

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Skip to 0 minutes and 5 seconds What do we mean by artificial intelligence? How will artificial intelligence transform healthcare? Can artificial intelligence give the gift of time back to health care professionals to focus on caring for patients and less time on mundane and repetitive administrative tasks? Is artificial intelligence a replacement or a colleague? These are just some of the questions you’ll be encouraged to explore in this course. The University of Manchester and Health Education England have come together to deliver a MOOC on artificial intelligence. The Topol Review published in February 2019, outlined that within 20 years, 90% of all jobs in the National Health Service will require some elements of digital skills. But where are we now?

Skip to 0 minutes and 54 seconds What do we need to support education and training in healthcare? We need a workforce that is able to take an active role in the development of AI in healthcare that can critically appraise and interpret the growth and impact of AI and robotic technologies. At Health Education England, our vision is to support digital transformation. And to have access to the right knowledge and evidence at the right time in the right place. And to enable high quality decision making.

Skip to 1 minute and 23 seconds At The University of Manchester, we are working with local NHS Trusts and national partners to understand how to best support the educational needs for the digital transformation of healthcare. This course will bring artificial intelligence to life by providing real world case studies, including exemplars from local health care partners. Here at The Christie We recognise the strategic importance of artificial intelligence to our future development. We are building academic collaborations and capacity to help us transform services and improve the patient experience. We will introduce you to artificial intelligence and machine learning. And look at what is motivating artificial intelligence in healthcare. In week three, we’ll be looking at the importance of the data in realising the potential of artificial intelligence.

Skip to 2 minutes and 12 seconds Week four will focus on some real examples where artificial intelligence has been embedded in the healthcare sector to highlight the roles, teams, and ethical requirements needed to make it all work in practice. Finally, in week five, you’ll have the opportunity to apply your knowledge of artificial intelligence and machine learning using a real world scenario. We will also hear how health care professionals have embarked on developing their own digital skills to transform how they work. We hope you enjoy the course, can contribute to the discussions on artificial intelligence, get some practical tools and guidance to support your own development, and be truly part of the digital transformation of healthcare.

Syllabus

  • Week 1

    Motivating AI in healthcare

    • Getting Started

      In this section, the course educators will welcome you to the course and you will start to think about what you know about AI and its application for healthcare.

    • Joining the Conversation

      In this section, we look at some of the new terminology you will come across in this field.

    • The Fourth Industrial Revolution

      In this section, we will look at some of the current uses of AI in healthcare and the impact of AI on your own area of expertise.

  • Week 2

    What is artificial intelligence?

    • AI and machine learning

      Artificial Intelligence and Machine Learning (ML) are two terms that are often used interchangeably. But, do they mean the same thing?

    • Machine learning workflow

      This section looks at the machine learning workflow process and looks at how machine learning can create value in your role.

    • Data in the machine learning workflow

      This section looks at the risks of imposing our biases on machine learning models used for decision-making purposes.

  • Week 3

    Data in healthcare

    • Challenges

      In this section, we explore the data within the healthcare ecosystem. We investigate the challenges of having untidy data that are not machine-readable and the effect on a machine learning (ML) workflow.

    • How data is being used

      In this section, we look at the different ways that data is being used in AI workflows to address different healthcare issues through examining our case studies.

    • Towards the future

      In this section, we look at ways that we can unlock innovations around data-driven health and social care services and the role you will play in making this happen.

  • Week 4

    Making it work

    • Ethics and consent

      In this section, we look at some of the ethical concerns of collecting patient data to use in a machine learning workflow.

    • Working in interdisciplinary teams

      In this section, we look at how AI projects benefit from working in interdisciplinary teams through examining some of our case studies.

    • New ways of working

      In this section, we look at the benefits and challenges of using a team science model in healthcare.

  • Week 5

    Supporting and skilling the workforce

    • Using machine learning for cancer diagnosis

      In this section, we will look at a practical example of AI in action to demonstrate how we can use machine learning to diagnose cancer. You will also have an opportunity to see if you can improve the performance of the algorithm.

    • Translation into practice

      In this section, we look at the implications of AI in healthcare and how it can and will transform practice. Is AI a replacement or a colleague? We would love to hear your thoughts.

    • Looking ahead

      Now that AI is here, what can you do to prepare yourself to be part of the digitally ready workforce?

When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.

  • Available now

What will you achieve?

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

  • Describe the benefits and challenges of Artificial Intelligence (AI) in healthcare across the broader spectrum of the health sector
  • Explore the concepts, ethical principles and approaches of AI within healthcare
  • Investigate the challenges and opportunities of data in healthcare to transform patient care
  • Explore the roles, teams and skills required to enable AI in healthcare
  • Apply learning to authentic and practice-based case studies which look at a range of applications of AI
  • Develop current practice, skills and knowledge to support recommendations from the Topol Review

Who is the course for?

This course is designed for health and social care professionals in the UK.

It is relevant to any non-UK healthcare professionals who want to understand the basic concepts, challenges and opportunities of AI in their respective healthcare systems.

The course is also useful for those with relevant skills outside the NHS who have an interest in new professional groups emerging from AI, such as clinical data scientists, medical software engineers, and digital medicine specialists.

Who will you learn with?

A professor of Bioinformatics at the University of Manchester who has been excited about AI, data science and interdisciplinary education in bioinformatics for over 20 years.

Ang Davies is a Senior Lecturer in Clinical Bioinformatics and Genomics at The University of Manchester and leads masters level programmes in these areas

Alan Davies is a lecturer in Health Data Sciences at the University of Manchester and teaches on masters level programmes in Health Data Science and Health Informatics.

Lecturer in Healthcare Sciences at The University of Manchester with a background in computer science. Now specialising in health informatics and socio-technical factors affecting data landscapes.

Research Associate specialising in medical imaging at the University of Manchester. Passionate about AI/Machine Learning and how it can benefit society.

Who developed the course?

The University of Manchester

From splitting the atom to giving the world graphene, The University of Manchester has a history of world firsts and brilliant discoveries.

Health Education England

Health Education England (HEE) support the delivery of excellent healthcare and health improvements to the patients and public of England.

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