The potential of Artificial Intelligence to predict heart disease: exploring AI to link electrocardiographic and metabolic biomarkers in individuals at risk of heart disease

About the Project

Ischaemic heart disease is the leading cause of mortality worldwide [1] and is increasingly prevalent in regions such as the USA and UK [2, 3]. The growing burden on public health systems is exacerbated by overlapping risk factors, including obesity, smoking, physical inactivity, hypertension, type II diabetes, and dyslipidaemia [4,5].

Diets low in omega-3 fatty acids are associated with an elevated risk of cardiovascular disease, while omega-3 rich diets offer protective benefits for the heart [6,7]. However, the precise mechanisms underlying this cardiovascular protection are not yet fully understood.

In the mid-1990s, researchers discovered that omega-3 reduce the electrical excitability of heart cells [8]. By the early 2000s, studies revealed that omega-3 consumption was positively correlated with a reduction in heart rate [9]. Despite these discoveries, their impact on overall cardiac function remained unclear until recently.

Our research group was the first to identify an inverse relationship between blood docosahexaenoic acid (DHA), a type of omega-3, and ventricular depolarization electrocardiographic (ECG) readouts in a population of healthy women [10]. Our findings offer a mechanistic explanation for the cardioprotective effects of omega-3 fatty acids by demonstrating that higher omega-3 levels improve the efficiency of the relationship between ventricular mass and its QRS voltage potential in healthy individuals.

The next step in our research is to explore these findings in larger population settings by integrating blood measurements, electrocardiographic markers, and artificial intelligence.

This project includes a pre-clinical component in which the PhD candidate will work directly with adults at risk of chronic metabolic diseases. The candidate will collect body composition data, electrocardiographic readings, and blood samples from consenting participants. Full training will be provided.

Applications are welcome from nutritionists, dietitians, clinical biochemists, or biomedical scientists, with excellent IT skills.

Supervisory team

This project is led by Dr Allain Bueno at the School of Sciences and the Environment. International collaborators from Spain and Brazil will also be involved in the research.

• Director of Studies: Dr Allain Bueno
• Supervisors: Dr Emma Edwards
• Research Group: Worcester Biomedical Research Group (WBRG)

Additional costs

Given that this is a laboratory-based project, bench fees will apply to cover the procurement of materials essential to delivering the research objectives. This will include consumables for the handling and processing of blood samples.

Application Process

To begin the application process please go to: https://www.worc.ac.uk/research/research-degrees/applying-for-a-phd/.

The Interview

All successful applicants will be offered an interview with the proposed Supervisory Team. You will be contacted by a member of the Doctoral School Team to find a suitable date. Interviews can be conducted in person or over Microsoft Teams.