Towards a lightweight generic computational grid framework for biological research. - Mark D. Halling-Brown; David S. Moss; Adrian J. Shepherd (BMC Bioinform., 2008)

The ImmunoGrid Simulator: How to Use It. - Francesco Pappalardo 001; Mark D. Halling-Brown; Marzio Pennisi; Ferdinando Chiacchio; Clare Sansom; Adrian J. Shepherd; David S. Moss; Santo Motta; Vladimir Brusic (CIBB, 2009)

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization. - Francesco Pappalardo 001; Mark D. Halling-Brown; Nicolas Rapin; Ping Zhang 008; Davide Alemani; Andrew P. J. Emerson; Paola Paci; Patrice Duroux; Marzio Pennisi; Arianna Palladini; Olivo Miotto; Daniel Churchill; et al. (Briefings Bioinform., 2009)

canSAR: an integrated cancer public translational research and drug discovery resource. - Mark D. Halling-Brown; Krishna C. Bulusu; Mishal N. Patel; Joe E. Tym; Bissan Al-Lazikani (Nucleic Acids Res., 2012)

Mammographic Image Database (MIDB) and Associated Web-Enabled Software for Research. - Mark D. Halling-Brown; Padraig T. Looney; Mishal N. Patel; Lucy M. Warren; Alistair Mackenzie; Kenneth C. Young (Digital Mammography / IWDM, 2014)

A Pilot Study on the Development of Remote Quality Control of Digital Mammography Systems in the NHS Breast Screening Programme. - Padraig T. Looney; Mark D. Halling-Brown; Jennifer M. Oduko; Kenneth C. Young (J. Digit. Imaging, 2015)

Impact of two types of image processing on cancer detection in mammography. - Lucy M. Warren; Mark D. Halling-Brown; Padraig T. Looney; David R. Dance; Louise Wilkinson; Matthew G. Wallis; Rosalind M. Given-Wilson; Julie Cooke; Rita McAvinchey; Kenneth C. Young (Image Perception, Observer Performance, and Technology Assessment, 2016)

A Deep Learning Model Observer for use in Alterative Forced Choice Virtual Clinical Trials. - Majdi R. Alnowami; G. Mills; M. Awis; Premkumar Elangovan; Mishal N. Patel; Mark D. Halling-Brown; Kenneth Y. Young; David R. Dance; Kevin Wells (Image Perception, Observer Performance, and Technology Assessment, 2018)

Using deep machine learning to detect esophageal lesions in PET-CT scans. - Ian Ackerley; Rhodri Smith; James W. Scuffham; Mark D. Halling-Brown; Emma Lewis; Emiliano Spezi; V. Prakash; Kevin Wells (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Using transfer learning for a deep learning model observer. - W. Murphy; Premkumar Elangovan; Mark D. Halling-Brown; Emma Lewis; K. C. Young; David R. Dance; Kevin Wells (Image Perception, Observer Performance, and Technology Assessment, 2019)

Changes in breast density. - Lucy M. Warren; Mark D. Halling-Brown; Louise S. Wilkinson; Rosalind M. Given-Wilson; Rita McAvinchey; Matthew G. Wallis; David R. Dance; K. C. Young (Image Perception, Observer Performance, and Technology Assessment, 2019)

OPTIMAM Mammography Image Database: a large scale resource of mammography images and clinical data. - Mark D. Halling-Brown; Lucy M. Warren; Dominic Ward; Emma Lewis; Alistair Mackenzie; Matthew G. Wallis; Louise Wilkinson; Rosalind M. Given-Wilson; Rita McAvinchey; Kenneth C. Young (CoRR, 2020)