- Email: email@example.com
- Thesis title: AI analysis of voice to aid laryngeal cancer diagnosis.
- Supervisor: Dr Luisa Cutillo, Mr James Moor (Leeds Teaching Hospitals NHS Trust)
Mary 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 starting this programme, Mary completed an integrated Masters in Electronic and Electrical Engineering at the University of Birmingham in 2020. Throughout her undergraduate degree, Mary was supported by the IET Diamond Jubilee Scholarship through which she worked two summers with Siemens Mobility.
Mary’s research focuses on improving diagnostic tools for head and neck cancer patients referred on the NHS 2 Week Wait pathway. With an aim to reduce the need for invasive medical procedures, machine learning will be used to assess patient’s voices in order to aid clinical decision making as to whether the larynx is a site of potential cancer development or whether it is affected by a wide range of non-cancer diagnoses.
- MEng Electronic and Electrical Engineering (University of Birmingham)