Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life. - Danielle Belgrave; Rachel Cassidy; Daniel Stamate; Adnan Custovic; Louise Fleming; Andrew Bush; Sejal Saglani (ICMLA, 2017)

Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning. - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Ida M. Pu; Fionn Murtagh; Danielle Belgrave; Robin M. Murray; Marta Di Forti (IPMU (3), 2018)

Understanding Client Support Strategies to Improve Clinical Outcomes in an Online Mental Health Intervention. - Prerna Chikersal; Danielle Belgrave; Gavin Doherty; Angel Enrique; Jorge E. Palacios; Derek Richards; Anja Thieme (CHI, 2020)

Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification. - James Jordon; Daniel Jarrett; Evgeny Saveliev; Jinsung Yoon; Paul W. G. Elbers; Patrick Thoral; Ari Ercole; Cheng Zhang 005; Danielle Belgrave; Mihaela van der Schaar (NeurIPS (Competition and Demos), 2020)

Hide-and-Seek Privacy Challenge. - James Jordon; Daniel Jarrett; Jinsung Yoon; Tavian Barnes; Paul W. G. Elbers; Patrick Thoral; Ari Ercole; Cheng Zhang 005; Danielle Belgrave; Mihaela van der Schaar (CoRR, 2020)

Causal Discovery for Causal Bandits utilizing Separating Sets. - Arnoud A. W. M. de Kroon; Danielle Belgrave; Joris M. Mooij (CoRR, 2020)

Machine learning applications: reflections on mental health assessment and ethics. - Anja Thieme; Danielle Belgrave; Akane Sano; Gavin Doherty (Interactions, 2020)

Machine Learning in Mental Health: A Systematic Review of the HCI Literature to Support the Development of Effective and Implementable ML Systems. - Anja Thieme; Danielle Belgrave; Gavin Doherty (ACM Trans. Comput. Hum. Interact., 2020)

Causal Bandits without prior knowledge using separating sets. - Arnoud A. W. M. de Kroon; Joris M. Mooij; Danielle Belgrave (CLeaR, 2022)

Generative models improve fairness of medical classifiers under distribution shifts. - Ira Ktena; Olivia Wiles; Isabela Albuquerque; Sylvestre-Alvise Rebuffi; Ryutaro Tanno; Abhijit Guha Roy; Shekoofeh Azizi; Danielle Belgrave; Pushmeet Kohli; Alan Karthikesalingam; A. Taylan Cemgil; Sven Gowal (CoRR, 2023)

Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other Experiments. - Alexander Goldberg; Ivan Stelmakh; Kyunghyun Cho; Alice H. Oh; Alekh Agarwal; Danielle Belgrave; Nihar B. Shah (CoRR, 2023)

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation. - Ryutaro Tanno; David G. T. Barrett; Andrew Sellergren; Sumedh Ghaisas; Sumanth Dathathri; Abigail See; Johannes Welbl; Karan Singhal; Shekoofeh Azizi; Tao Tu 001; Mike Schaekermann; Rhys May; et al. (CoRR, 2023)

Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task. - Jannik Kossen; Catalina Cangea; Eszter Vértes; Andrew Jaegle; Viorica Patraucean; Ira Ktena; Nenad Tomasev; Danielle Belgrave (Trans. Mach. Learn. Res., 2023)

Information Transfer Across Clinical Tasks via Adaptive Parameter Optimisation. - Anshul Thakur; Elena Gal; Soheila Molaei; Xiao Gu 003; Patrick Schwab; Danielle Belgrave; Kim Branson 001; David A. Clifton (AISTATS, 2025)

Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation. - Anshul Thakur; Soheila Molaei; Patrick Schwab; Danielle Belgrave; Kim Branson 001; David A. Clifton (AISTATS, 2025)