Emma 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 the CDT, Emma graduated with an MSc in Health Informatics from the Karolinska Institute and Stockholm University in Stockholm, Sweden (2020), where Emma completed projects applying data science to problems in healthcare, for example investigating ways of mitigating discrimination in clinical machine-learning resource-allocation tools using algorithmic processing techniques. During this time she also worked for EIT Health helping to develop online courses for informal caregivers of older adults, focusing on user experience. Emma continues to pursue her interest in data-driven decision making in healthcare at Leeds.
Emma’s primary area of research is investigating how AI might improve clinical risk-prediction tools, particularly for estimating cancer risk to facilitate earlier diagnosis of common cancers in primary care. The focus is especially on cancers with vague manifestations and limited screening opportunities, such as oesophago-gastric cancer and pancreatic cancer. The aim is to generate more individualised risk scores and flag potential cancer cases that might otherwise have been missed, using AI to exploit the wealth of information available in the electronic health record. This research is supported by TPP and Macmillan and aligns with NHS strategies to diagnose 75% of all cancers at stage 2 or earlier by 2028.
Emma’s research interests are summarised below.
- AI for expediting cancer diagnosis in primary care
- AI for clinical risk prediction and clinical decision support
- Fairness in AI-based clinical decision making
- MSc Health Informatics, Karolinska Institutet & Stockholm University, Stockholm, Sweden, 2020
- BSc Discrete Mathematics, University of Warwick, 2018