Eloise Ockenden
Postdoctoral Researcher
I am a Postdoctoral Researcher in Biomedical Image Analysis within the SchistoTrack group, working on clinical decision support for schistosomiasis-induced periportal fibrosis. I recently finished my DPhil entitled 'Applications of machine learning for staging of schistosomiasis-induced periportal fibrosis using point-of-care ultrasound from a rural Ugandan cohort', supervised by Professors Goylette Chami and Alison Noble. During my DPhil, I developed deep learning-based models for classification of patterns of periportal fibrosis on ultrasound images and video.
Before my DPhil, I studied for my Master’s in Mathematics at Durham. My master’s project combined machine learning and healthcare, classifying features of breast masses that would indicate malignancy.
In my spare time, I enjoy baking, crochet, and playing the clarinet!
Recent publications
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
Preprint
Ockenden E. et al, (2026)
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
Preprint
Ockenden E. et al, (2026)
Patient journeys for neglected tropical diseases in rural sub-Saharan Africa: a scoping review.
Journal article
Frischer SR. et al, (2025), Infectious diseases of poverty, 14
The role of point-of-care ultrasound in the assessment of schistosomiasis-induced liver fibrosis: A systematic scoping review.
Journal article
Ockenden ES. et al, (2024), PLoS neglected tropical diseases, 18
Conceptualising care pathways for neglected tropical diseases in sub-Saharan Africa: A systematic scoping review
Preprint
Frischer SR. et al, (2024)