Alexander Coles
- Email: scadc@leeds.ac.uk
- Thesis title: Detection of Recurrence in Cancer Patients
- Supervisor: Owen Johnson, Geoff Hall
Profile
Alexander has been a Postgraduate Research Student on the UKRI Centre for Doctoral Training (CDT) in Artificial Intelligence for Medical Diagnosis and Care at The University of Leeds since 2020. Prior to joining this programme, Alexander graduated with an MSci in Physics with Astronomy from the University of Nottingham (2019).
Research interests
Alexander’s primary area of research is in the detection of recurrence in cancer patients. Cancer recurrence is poorly documented in a patient’s electronic health record (EHR). Clinicians often only record the recurrence of a patient’s cancer within the written case notes of their EHR. Therefore, without an in-depth analysis of a patient’s unstructured records, it is difficult to perform research into the causes and treatment pathways leading up to a cancer recurrence event. Alexander’s research aims to detect cancer recurrence events from the structured data recorded in a patient’s EHR using multiple data mining methods. Some of these methods include:
- Recurrent AI
- Random Forests
- Process Mining
Qualifications
- MSci Physics with Astronomy, University of Nottingham, 2019