Detection of Mixed Infection from Bacterial Whole Genome Sequence Data Allows Assessment of Its Role in Clostridium difficile Transmission. - David W. Eyre; Madeleine L. Cule; David Griffiths; Derrick W. Crook; Tim E. A. Peto; A. Sarah Walker; Daniel J. Wilson 001 (PLoS Comput. Biol., 2013)

BugMat and FindNeighbour: command line and server applications for investigating bacterial relatedness. - Oriol Mazariegos-Canellas; Trien Do; Tim E. A. Peto; David W. Eyre; Anthony Underwood; Derrick W. Crook; David H. Wyllie (BMC Bioinform., 2017)

Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location. - Rasheed el-Bouri; David W. Eyre; Peter J. Watkinson; Tingting Zhu 001; David A. Clifton (ICML, 2020)

Probabilistic transmission models incorporating sequencing data for healthcare-associated Clostridioides difficile outperform heuristic rules and identify strain-specific differences in transmission. - David W. Eyre; Mirjam Laager; A. Sarah Walker; Ben S. Cooper; Daniel J. Wilson 001 (PLoS Comput. Biol., 2021)

Hospital Admission Location Prediction via Deep Interpretable Networks for the Year-Round Improvement of Emergency Patient Care. - Rasheed el-Bouri; David W. Eyre; Peter J. Watkinson; Tingting Zhu 001; David A. Clifton (IEEE J. Biomed. Health Informatics, 2021)

Infectious disease surveillance needs for the United States: lessons from COVID-19. - Marc Lipsitch; Mary T. Bassett; John S. Brownstein; Paul Elliott; David Eyre 001; M. Kate Grabowski; James A. Hay; Michael A. Johansson; Stephen M. Kissler; Daniel B. Larremore; Jennifer Layden; Justin Lessler; et al. (CoRR, 2023)

An adversarial training framework for mitigating algorithmic biases in clinical machine learning. - Jenny Yang; Andrew A. S. Soltan; David W. Eyre; Yang Yang 125; David A. Clifton (npj Digit. Medicine, 2023)

Self-Aware SGD: Reliable Incremental Adaptation Framework for Clinical AI Models. - Anshul Thakur; Jacob Armstrong; Alexey Youssef; David W. Eyre; David A. Clifton (IEEE J. Biomed. Health Informatics, 2023)

Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning. - Jenny Yang; Andrew A. S. Soltan; David W. Eyre; David A. Clifton (Nat. Mac. Intell., 2023)

Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. - Jenny Yang; Rasheed El-Bouri; Odhran O'Donoghue; Alexander S. Lachapelle; Andrew A. S. Soltan; David W. Eyre; Lei Lu; David A. Clifton (Mach. Learn., 2024)

Tree-of-Quote Prompting Improves Factuality and Attribution in Multi-Hop and Medical Reasoning. - Justin Xu; Yiming Li; Zizheng Zhang; Augustine Yui Hei Luk; Mayank Jobanputra; Samarth Oza; Ashley Murray; Meghana Reddy Kasula; Andrew Parker; David W. Eyre (EMNLP, 2025)

RadEval: A framework for radiology text evaluation. - Justin Xu; Xi Zhang 025; Javid Abderezaei; Julie Bauml; Roger Boodoo; Fatemeh Haghighi; Ali Ganjizadeh; Eric Brattain; Dave Van Veen; Zaiqiao Meng; David W. Eyre; Jean-Benoit Delbrouck (EMNLP (System Demonstrations), 2025)

MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Clinical Tabular Prediction. - Zizheng Zhang; Yiming Li; Justin Xu; Jinyu Wang; Rui Wang 028; Lei Song 001; Jiang Bian 002; David W. Eyre; Jingjing Fu (CoRR, 2026)

SignalMC-MED: A Multimodal Benchmark for Evaluating Biosignal Foundation Models on Single-Lead ECG and PPG. - Fredrik K. Gustafsson; Xiao Gu 003; Mattia Carletti; Patitapaban Palo; David W. Eyre; David A. Clifton (CoRR, 2026)