Artificial Intelligence in Healthcare

Artificial intelligence (AI) is the construction of artificial systems that have intelligent behaviour. They can be used as drug candidate detection in medicine or cancer recognition from scans which have had previous successes but the opportunities in the wider healthcare field are still to be explored. Modern health services have also been transformed by e-referrals, the NHS app and Covid-19 risk stratification.

Healthcare is delivered in a complex system, and you can gain an understanding of the system, some key health conditions and their care plans. You will also learn to understand the various agencies and their interoperation in supporting the patient as well as the patient’s environment.

By studying this course, you can be equipped to use leading-edge science and data to contribute to improving digital transformation in healthcare. This course puts human-centred design, agility, and a solutions-focused approach at the heart of your learning.

You will consider patient care, diagnosis, treatment, and pharma links within the context of both a clinical and an AI environment. In a clinical and data setting, you will be supported to gain a biomedical, physiological, and social understanding and knowledge. You will also develop the digital, clinical, and data skills to ensure you can contribute to the digital transformation which will be at the heart of healthcare of the future.

This course can position you at the cutting edge of this graduate job market. You will graduate with the skills to tackle some of the biggest challenges in the study of human health and machine behaviour, whilst applying your knowledge to offer future-focused solutions.

Interdisciplinary learning

This degree has been designed to offer an interdisciplinary programme, where you will join debates based on topics covered by the core modules and you will come together with all AI pathways to explore the opportunities and risks, as well as societal and ethical implications of AI technologies. This aims to bring together a varied insight in how other disciplines are considering the use of AI.

Combine this, with lectures from industry experts from the NHS, undertaking an Industrial Placement Year and hands-on practical experience using specialist equipment and you could graduate feeling confident and able to find solutions for current issues.

On this course, you will:

• Explore how AI can be applied in a healthcare setting and delve into the ethics of using AI, how can and should it be used, what are the issues and how do we effectively use AI tools
• Develop an understanding of the most common physical and mental health conditions, key interventions for treatment and care, and discuss how social inequality creates social division across society
• Undertake a research project in a chosen topic area in the fields of Health & Social Care and Health Promotion
• Critically analyse and reflect on the application of organisational structures, policies, management processes, skills, roles and responsibilities in the design and management of health and social care services and discuss the impact on the individual, their family, friends, carers of interventions and necessary treatments of care available in modern UK

Expert teaching

You will learn from lecturers and tutors who are carrying out research designed to offer fresh perspectives on issues that are significant at every stage of life as well as those who develop and apply the latest AI tools in domains ranging from health to manufacturing. Your lecturers bring their latest thinking to your studies. And, in some cases, you will have opportunities to get involved in research projects yourself.

Please note that our modules are subject to change - we review the content of our courses regularly, making changes where necessary to improve your experience and graduate prospects.

Our teaching methods consist of:

• lectures
• seminars
• practical sessions
• group working
• visits to exhibitions, trade fairs and companies
• research projects
• internships and/or placements
• case studies, briefs, projects or scenarios from real workplaces

How you will be assessed

Modules are normally assessed through a mixture of:

• assignments
• examinations
• workshops
• class tests
• practical labs
• coursework
• portfolios
• assignments
• case studies
• oral and graphic presentations
• teamwork projects
• computer testing
• examinations

The Individual Project module encourages students to use and apply research and innovation tools and approaches in a practical context. Sustainability thinking is integral to several modules.

You will graduate with the skills to tackle some of the biggest challenges in the study of human health and machine behaviour, whilst applying your knowledge to offer future-focused solutions. This course can position you at the cutting edge of this graduate job market where you can apply your skills, knowledge and expertise to maximise the opportunities that this new technology will provide.

Contextual offers may apply to students who meet certain criteria.

Further information about our fees and support you may be entitled to

Additional information about your studies

Teaching hours

Like most universities, we operate extended teaching hours at the University of Derby, so contact time with your lecturers and tutors could be anytime between 9am and 9pm. Your timetable will usually be available on the website 24 hours after enrolment on to your course.

Course updates

The information provided on this page is correct at the time of publication but course content, costs and other individual course details do change from time to time and are updated as often as possible, so please do check these pages again when making your final decision to apply for a course. Any updated course details will also be confirmed to you at application, enrolment and in your offer letter.

If you are thinking about transferring onto this course (into the second year for example), you should contact the programme leader for the relevant course information as modules may vary from those shown on this page.

Minimum numbers

Please note that this course is subject to minimum numbers in order to run.