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Mark D Halling-Brown

Showing results (1-10 of 14) with videos related to

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BMC Bioinformatics|October 4, 2008
Towards a lightweight generic computational grid framework for biological researchMark D Halling-Brown, David S Moss, Adrian J Shepherd
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|June 3, 2009
A computational Grid framework for immunological applicationsMark D Halling-Brown, David S Moss, Clare E Sansom, et al.
BJR Artificial Intelligence|May 22, 2026
Development and evaluation of artificial intelligence tools to estimate volumetric breast density from processed 2D mammogramsSam Ellis, Sandra Gomes, Mark D Halling-Brown, et al.
Nucleic Acids Research|October 21, 2011
canSAR: an integrated cancer public translational research and drug discovery resourceMark D Halling-Brown, Krishna C Bulusu, Mishal Patel, et al.
Nature Reviews. Drug Discovery|January 1, 2013
Objective assessment of cancer genes for drug discoveryMishal N Patel, Mark D Halling-Brown, Joseph E Tym, et al.
Journal of Molecular Graphics & Modelling|September 4, 2007
Toward the atomistic simulation of T cell epitopes automated construction of MHC: peptide structures for free energy calculationsSarah J Todman, Mark D Halling-Brown, Matthew N Davies, et al.
Radiology. Artificial Intelligence|May 22, 2024
Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening CohortSam Ellis, Sandra Gomes, Matthew Trumble, et al.
Radiology. Artificial Intelligence|May 3, 2021
OPTIMAM Mammography Image Database: A Large-Scale Resource of Mammography Images and Clinical DataMark D Halling-Brown, Lucy M Warren, Dominic Ward, et al.
AJR. American Journal of Roentgenology|July 24, 2014
The effect of image processing on the detection of cancers in digital mammographyLucy M Warren, Rosalind M Given-Wilson, Matthew G Wallis, et al.
European Radiology|June 25, 2015
Breast cancer detection rates using four different types of mammography detectorsAlistair Mackenzie, Lucy M Warren, Matthew G Wallis, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|October 4, 2008
Towards a lightweight generic computational grid framework for biological researchMark D Halling-Brown, David S Moss, Adrian J Shepherd
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|June 3, 2009
A computational Grid framework for immunological applicationsMark D Halling-Brown, David S Moss, Clare E Sansom, et al.
BJR Artificial Intelligence|May 22, 2026
Development and evaluation of artificial intelligence tools to estimate volumetric breast density from processed 2D mammogramsSam Ellis, Sandra Gomes, Mark D Halling-Brown, et al.
Nucleic Acids Research|October 21, 2011
canSAR: an integrated cancer public translational research and drug discovery resourceMark D Halling-Brown, Krishna C Bulusu, Mishal Patel, et al.
Nature Reviews. Drug Discovery|January 1, 2013
Objective assessment of cancer genes for drug discoveryMishal N Patel, Mark D Halling-Brown, Joseph E Tym, et al.
Journal of Molecular Graphics & Modelling|September 4, 2007
Toward the atomistic simulation of T cell epitopes automated construction of MHC: peptide structures for free energy calculationsSarah J Todman, Mark D Halling-Brown, Matthew N Davies, et al.
Radiology. Artificial Intelligence|May 22, 2024
Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening CohortSam Ellis, Sandra Gomes, Matthew Trumble, et al.
Radiology. Artificial Intelligence|May 3, 2021
OPTIMAM Mammography Image Database: A Large-Scale Resource of Mammography Images and Clinical DataMark D Halling-Brown, Lucy M Warren, Dominic Ward, et al.
AJR. American Journal of Roentgenology|July 24, 2014
The effect of image processing on the detection of cancers in digital mammographyLucy M Warren, Rosalind M Given-Wilson, Matthew G Wallis, et al.
European Radiology|June 25, 2015
Breast cancer detection rates using four different types of mammography detectorsAlistair Mackenzie, Lucy M Warren, Matthew G Wallis, et al.
Pageof 2