Hello! I'm Zoe Hancox, a Postdoctoral Researcher at the University of Leeds. If I'm not working you'll find me doing yoga, cuddling my cat, jogging, gardening, reading dystopian or fantasy novels, or making wacky greeting cards.
PREDICT (Pragmatic Recalibration and Evaluation of Drift In Clinical Tools)
• Developing algorithms to detect and correct temporal drift in clinical prediction models.
• Applying models to QRISK and eFalls using clinical data.
• Engaging with patients and stakeholders.
What is temporal drift?
What causes temporal drift?
My PhD research revolved around using graphs (also called networks, the kind where nodes are linked via edges) to analyse data or make predictions of health outcomes. In particular creating temporal graphs and applying 3D convolutional neural networks to make predictions of health outcomes such as hip replacement using patient historical electronic healthcare records.
This thesis introduces a Temporal Graph‑Based Convolutional Neural Network (TG‑CNN) that models Electronic Health Records as temporal graphs to predict hip and knee replacement risk up to five years in advance, achieving AUROC scores as high as 0.967. While the model delivers strong predictive performance, further work on explainability is needed to support its translation into real‑world clinical decision‑making.
Teaching: Co-lead on the ‘Artificial Intelligence and Machine Learning in Health’ module at the University of Leeds. I also supervise MSc students in their final health informatics and data science projects.
LIDA Health Early Career Researchers Committee Co-lead: Host and organise workshops on research enhancement and technical skills, health research talks, and career development sessions for ECRs.
Data Scientist at NHS England: We transformed healthcare data using graph-based techniques using SAIL DataBank data. Hypergraphs were applied to study multimorbidity pathways, helping to reveal complex relationships between conditions. The results were shared NHS-wide and made publicly available through an open repository and report. Learn more about how hypergraphs work and how to use them in this context via our interactive Streamlit app.
Applications and Implications of Artificial Intelligence (AI^2) President: I was one of the conceptualisers and founders of the Applications and Implications of Artificial Intelligence (AI^2) Forum at the University of Leeds.
What is the AI^2 forum? The Applications and Implications of Artificial Intelligence (AI^2) forum aims to bring students and researchers together to talk about different areas of AI and data science. It is used to encourage likeminded researchers to network and give people the opportunity to deepen their knowledge and share ideas. This forum is held on the last Wednesday of every month from 4-6pm. Sessions are also held with representatives from industry, where these representatives speak about their career pathway, the company they work at and any work they are undertaking that uses AI.
If you want to find out more you can read our blog summarising some of our sessions.
Journal Club Co-Chair: I co-chaired and helped arrange weekly journal clubs for the CDT.