Explainable AI to ensure trust in clinical Decision Support Systems (ExAIDSS)

Technological breakthroughs have led to the development of sophisticated healthcare systems, but these will only become widely adopted if patients and healthcare professionals have confidence in their recommendations. Without a solution to the problem of user trust and user acceptance of healthcare technologies generally, the undeniable benefits of these systems will never be realised and all our efforts to develop accurate health-AI will be in vain. The ‘right to explanation’ and regulations on algorithmic decision-making already exist. Therefore, the ExAIDSS project focuses on translating causal AI models into explainable AI systems that users can trust and adopt in healthcare. The objectives of the project are:

1. Investigate the fundamentals of explanation: Explore fundamental questions that have been neglected, such as what makes an explanation of AI “good”.
2. Develop explanation algorithms that incorporate causality: Develop explanation algorithms that produces meaningful causal explanations for various types of reasoning.
3. Create user-specific explanation outputs: Design an explanation that recognises who is interacting with it and the dynamics of clinical decision making.
4. Create an evaluation protocol: Propose a protocol for evaluating different explanations purposes.
5. Integrate the explanation algorithm and representation into existing healthcare digital platforms.

The successful candidate will work on some of the above objectives. The project may build on prior research by the supervision team on topics such as AI adoption in healthcare and explainable AI. More details can be found in https://exaidss.com/. There are also many opportunities for new directions. The project may focus on theoretical or practical aspects, or a combination thereof.

The PhD student will be supported by a QM Principal Studentship. They will receive tuition fees and a London stipend at UKRI rates (currently in 2024/25 of £21,237 per year, to be confirmed for 2025/26) annually during the PhD period, which can span for 3 years.

For more information about the project, please contact Evangelia Kyrimi (e.kyrimi@qmul.ac.uk).

Supervisor

Dr Evangelia Kyrimi – e.kyrimi@qmul.ac.uk

https://www.qmul.ac.uk/eecs/people/profiles/kyrimievangelia.html

Google Scholar: https://scholar.google.com/citations?user=ApdIq1YAAAAJ&hl=en

How to apply 

Queen Mary is interested in developing the next generation of outstanding researchers and decided to invest in specific research areas. For further information about potential PhD projects and supervisors please see the list of the projects at the end of this page.

Applicants should work with their prospective supervisor and submit their application following the instructions at: http://eecs.qmul.ac.uk/phd/how-to-apply/  

The application should include the following: 

• CV (max 2 pages)
• Cover letter (max 4,500 characters) stating clearly in the first page whether you are eligible for a scholarship as a UK resident (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)
• Research proposal (max 500 words)
• 2 References
• Certificate of English Language (for students whose first language is not English)
• Other Certificates

Please note that to qualify as a home student for the purpose of the scholarships, a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship. For more information please see: (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)  

Application Deadline 

The deadline for applications is the 22^nd November 2024. 

For general enquiries contact Mrs Melissa Yeo at m.yeo@qmul.ac.uk (administrative enquiries) or Dr Arkaitz Zubiaga at a.zubiaga@qmul.ac.uk (academic enquiries) with the subject “EECS 2025 PhD scholarships enquiry”. 

For specific enquiries contact Dr Evangelia Kyrimi at e.kyrimi@qmul.ac.uk