Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. - Michael Roberts; Derek Driggs; Matthew Thorpe; Julian D. Gilbey; Michael Yeung; Stephan Ursprung; Angelica I. Avilés-Rivero; Christian Etmann; Cathal McCague; Lucian Beer; Jonathan R. Weir-McCall; Zhongzhao Teng; et al. (CoRR, 2020)

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. - Michael Roberts; Derek Driggs; Matthew Thorpe; Julian D. Gilbey; Michael Yeung; Stephan Ursprung; Angelica I. Avilés-Rivero; Christian Etmann; Cathal McCague; Lucian Beer; Jonathan R. Weir-McCall; Zhongzhao Teng; et al. (Nat. Mach. Intell., 2021)

Classification of datasets with imputed missing values: does imputation quality matter? - Tolou Shadbahr; Michael Roberts; Jan Stanczuk; Julian D. Gilbey; Philip Teare; Sören Dittmer; Matthew Thorpe; Ramón Viñas Torné 001; Evis Sala; Pietro Lió; Mishal Patel; AIX-COVNET Collaboration; et al. (CoRR, 2022)

Navigating the challenges in creating complex data systems: a development philosophy. - Sören Dittmer; Michael Roberts; Julian D. Gilbey; Ander Biguri; AIX-COVNET Collaboration; Jacobus Preller; James H. F. Rudd; John A. D. Aston; Carola-Bibiane Schönlieb (CoRR, 2022)

Dis-AE: Multi-domain & Multi-task Generalisation on Real-World Clinical Data. - Daniel Kreuter; Samuel Tull; Julian D. Gilbey; Jacobus Preller; BloodCounts Consortium; John A. D. Aston; James H. F. Rudd; Suthesh Sivapalaratnam; Carola-Bibiane Schönlieb; Nicholas S. Gleadall; Michael Roberts (CoRR, 2023)

Reinterpreting survival analysis in the universal approximator age. - Sören Dittmer; Michael Roberts; Jacobus Preller; AIX-COVNET Collaboration; James H. F. Rudd; John A. D. Aston; Carola-Bibiane Schönlieb (CoRR, 2023)

Recent Methodological Advances in Federated Learning for Healthcare. - Fan Zhang; Daniel Kreuter; Yichen Chen; Sören Dittmer; Samuel Tull; Tolou Shadbahr; BloodCounts Collaboration; Jacobus Preller; James H. F. Rudd; John A. D. Aston; Carola-Bibiane Schönlieb; Nicholas S. Gleadall; et al. (CoRR, 2023)

Navigating the development challenges in creating complex data systems. - Sören Dittmer; Michael Roberts; Julian D. Gilbey; Ander Biguri; Ian Selby; Anna Breger; Matthew Thorpe; Jonathan R. Weir-McCall; Effrossyni Gkrania-Klotsas; Anna Korhonen; Emily R. Jefferson; Georg Langs; et al. (Nat. Mac. Intell., 2023)

The curious case of the test set AUROC. - Michael Roberts; Alon Hazan; Sören Dittmer; James H. F. Rudd; Carola-Bibiane Schönlieb (Nat. Mac. Intell., 2024)

Publisher Correction: The curious case of the test set AUROC. - Michael Roberts; Alon Hazan; Sören Dittmer; James H. F. Rudd; Carola-Bibiane Schönlieb (Nat. Mac. Intell., 2024)

Recent methodological advances in federated learning for healthcare. - Fan Zhang; Daniel Kreuter; Yichen Chen; Sören Dittmer; Samuel Tull; Tolou Shadbahr; Martijn Schut; Folkert W. Asselbergs; Sujoy Kar; Suthesh Sivapalaratnam; Sophie Williams; Mickey Koh; et al. (Patterns, 2024)

Parameter Choices in Haarpsi for IQA with Medical Images. - Clemens Karner; Janek Gröhl; Ian Selby; Judith Babar; Jake Beckford; Thomas R. Else; Timothy J. Sadler; Shahab Shahipasand; Arthikkaa Thavakumar; Michael Roberts; James H. F. Rudd; Carola-Bibiane Schönlieb; et al. (ISBI, 2025)

SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events. - Yichen Kelly Chen; Sören Dittmer; Kinga Bernatowicz; Josep Arús-Pous; Kamen Bliznashki; John A. D. Aston; James H. F. Rudd; Carola-Bibiane Schönlieb; James Jones; Michael Roberts (CoRR, 2025)