M
Mark D. Halling-Brown
Researcher at Royal Surrey County Hospital
Publications - 58
Citations - 2229
Mark D. Halling-Brown is an academic researcher from Royal Surrey County Hospital. The author has contributed to research in topics: Mammography & Medicine. The author has an hindex of 15, co-authored 49 publications receiving 1335 citations. Previous affiliations of Mark D. Halling-Brown include Institute of Cancer Research & Birkbeck, University of London.
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International evaluation of an AI system for breast cancer screening.
Scott Mayer McKinney,Marcin Sieniek,Varun Godbole,Jonathan Godwin,Natasha Antropova,Hutan Ashrafian,Trevor Back,Mary Chesus,Greg C. Corrado,Ara Darzi,Mozziyar Etemadi,Florencia Garcia-Vicente,Fiona J. Gilbert,Mark D. Halling-Brown,Demis Hassabis,Sunny Jansen,Alan Karthikesalingam,Christopher Kelly,Dominic King,Joseph R. Ledsam,David S. Melnick,Hormuz Mostofi,Lily Peng,Joshua J. Reicher,Bernardino Romera-Paredes,Richard Sidebottom,Mustafa Suleyman,Daniel Tse,Kenneth C. Young,Jeffrey De Fauw,Shravya Shetty +30 more
TL;DR: A robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening and using a combination of AI and human inputs could help to improve screening efficiency.
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Objective assessment of cancer genes for drug discovery
TL;DR: An objective, systematic, multifaceted computational assessment of biological and chemical space that can be applied to any human gene set to prioritize targets for therapeutic exploration is described.
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canSAR: an integrated cancer public translational research and drug discovery resource.
TL;DR: CanSAR can, in a single place, rapidly identify biological annotation of a target, its structural characterization, expression levels and protein interaction data, as well as suitable cell lines for experiments, potential tool compounds and similarity to known drug targets.
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ImmunoGrid: towards agent-based simulations of the human immune system at a natural scale.
Mark D. Halling-Brown,Francesco Pappalardo,Nicolas Rapin,Ping Zhang,Davide Alemani,Andrew Emerson,Filippo Castiglione,Patrice Duroux,Marzio Pennisi,Olivo Miotto,Daniel Churchill,Elda Rossi,David S. Moss,Clare Sansom,Massimo Bernaschi,Marie-Paule Lefranc,Søren Brunak,Ole Lund,Santo Motta,Pier Luigi Lollini,Annalisa Murgo,Arianna Palladini,Kaye E. Basford,Vladimir Brusic,Vladimir Brusic,Adrian J. Shepherd +25 more
TL;DR: This paper explains the key challenges of the ImmunoGrid project, the approaches adopted to overcome them, and considers wider implications for the present ambitious plans to develop natural-scale, integrated models of the human body that can make contributions to personalized health care, such as the European Virtual Physiological Human initiative.
Journal ArticleDOI
GPCRTree: online hierarchical classification of GPCR function
Matthew N. Davies,Andrew Secker,Mark D. Halling-Brown,David S. Moss,Alex A. Freitas,Jon Timmis,Edward B. Clark,Darren R. Flower +7 more
TL;DR: GPCRTree, a publicly-available internet server, implements an algorithm that classifies GPCRs at the class, sub-family and sub-subfamily level, and is considerably more accurate at every level of classification.