Machine learning methods for diabetes patients’ data analysis

GTA funded PhD studentship in Computing

Highlights

1. Applying machine learning methods for diabetes patients’ healthcare
2. Access/analyse new data sets gathered in Leicester Diabetes Centre
3. Exploring correlation between patients’ glucose level and daily exercise

Project

Diabetes becomes a major threat to the health of a huge number of people worldwide. How to help diabetes patients to maintain and improve quality of life is critical important nowadays. However, the data collected from diabetes patients with wearable sensors such as glucose level and accelerometer often huge – not easy to be investigated by human eye or speculated the model underlying by simple calculation. Machine learning methods that are designed for processing large quantity of data sets, exploring the correlations between different patterns will play a significant role in this scenario. 

You will access the data set collected in Leicester Diabetes Centre, use appropriate machine learning methods to analyse the data set, to reveal patterns of daily exercise and the correlation to level of glucose and other indicators. New findings will be published in relevant conferences and journals. 

PhD start date 23 September 2024

Enquiries to project supervisor Professor Shigang Yue Sy237@leicester.ac.uk   or cmspgr@le.ac.uk

Further details and application advice at https://le.ac.uk/study/research-degrees/funded-opportunities/cms-gta