Towards a Framework for Teaching Debugging. - Chen Li; Emily Chan; Paul Denny 001; Andrew Luxton-Reilly; Ewan D. Tempero (ACE, 2019)

Comparison of Classical Machine Learning & Deep Learning to Characterise Fibrosis & Inflammation Using Quantitative MRI. - Emily Chan; Matt Kelly; Julia A. Schnabel (ISBI, 2021)

Automated Quality Controlled Analysis of 2D Phase Contrast Cardiovascular Magnetic Resonance Imaging. - Emily Chan; Ciaran O'Hanlon; Carlota Asegurado Marquez; Marwenie Petalcorin; Jorge Mariscal Harana; Haotian Gu; Raymond J. Kim; Robert M. Judd; Philip J. Chowienczyk; Julia A. Schnabel; Reza Razavi; Andrew P. King; et al. (STACOM@MICCAI, 2022)

Addressing Deep Learning Model Calibration Using Evidential Neural Networks and Uncertainty-Aware Training. - Tareen Dawood; Emily Chan; Reza Razavi; Andrew P. King; Esther Puyol-Antón (ISBI, 2023)

Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. - Maxime Di Folco; Cosmin I. Bercea; Emily Chan; Julia A. Schnabel (MICCAI (10), 2024)

Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders. - Mehmet Yigit Avci; Emily Chan; Veronika A. M. Zimmer; Daniel Rueckert; Benedikt Wiestler; Julia A. Schnabel; Cosmin I. Bercea (CoRR, 2024)

Semantic Alignment of Unimodal Medical Text and Vision Representations. - Maxime Di Folco; Emily Chan; Marta Hasny; Cosmin I. Bercea; Julia A. Schnabel (CoRR, 2025)