Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones. - Andrew P. Creagh; Florian Lipsmeier; Michael Lindemann; Maarten De Vos (CoRR, 2021)

Smartphone- and Smartwatch-Based Remote Characterisation of Ambulation in Multiple Sclerosis During the Two-Minute Walk Test. - Andrew P. Creagh; Cedric Simillion; Alan K. Bourke; Alf Scotland; Florian Lipsmeier; Corrado Bernasconi; Johan van Beek; Mike Baker; Christian Gossens; Michael Lindemann; Maarten De Vos (IEEE J. Biomed. Health Informatics, 2021)

Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression Modeling. - Taha Ceritli; Andrew P. Creagh; David A. Clifton (BHI, 2022)

Self-supervised Learning for Human Activity Recognition Using 700, 000 Person-days of Wearable Data. - Hang Yuan; Shing Chan; Andrew P. Creagh; Catherine Tong; David A. Clifton; Aiden R. Doherty (CoRR, 2022)

Synthesizing Mixed-type Electronic Health Records using Diffusion Models. - Taha Ceritli; Ghadeer O. Ghosheh; Vinod Kumar Chauhan; Tingting Zhu 001; Andrew P. Creagh; David A. Clifton (CoRR, 2023)

Personalized Longitudinal Assessment of Multiple Sclerosis Using Smartphones. - Oliver Y. Chén; Florian Lipsmeier; Huy Phan; Frank Dondelinger; Andrew P. Creagh; Christian Gossens; Michael Lindemann; Maarten De Vos (IEEE J. Biomed. Health Informatics, 2023)

2D-WinSpatt-Net: A Dual Spatial Self-Attention Vision Transformer Boosts Classification of Tetanus Severity for Patients Wearing ECG Sensors in Low- and Middle-Income Countries. - Ping Lu 003; Andrew P. Creagh; Huiqi Y. Lu; Ho Bich Hai; Louise Thwaites; David A. Clifton (Sensors, 2023)

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis. - Andrew P. Creagh; Valentin Hamy; Hang Yuan; Gert Mertes; Ryan Tomlinson; Wen-Hung Chen; Rachel Williams; Christopher Llop; Christopher Yee; Mei Sheng Duh; Aiden R. Doherty; Luis Garcia-Gancedo; et al. (npj Digit. Medicine, 2024)

Self-supervised learning for human activity recognition using 700,000 person-days of wearable data. - Hang Yuan; Shing Chan; Andrew P. Creagh; Catherine Tong; Aidan Acquah; David A. Clifton; Aiden R. Doherty (npj Digit. Medicine, 2024)