All Outputs (56)

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer (2014)
Journal Article
Rakha, E., Soria, D., Green, A. R., Lemetre, C., Powe, D. G., Nolan, C. C., …Ellis, I. O. (2014). Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer. British Journal of Cancer, 110(7), https://doi.org/10.1038/bjc.2014.120

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. I... Read More about Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs (2014)
Journal Article
Reps, J., M. Garibaldi, J., Aickelin, U., Soria, D., E. Gibson, J., & B. Hubbard, R. (2014). Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs. Drug Safety, 37(3), 163-170. https://doi.org/10.1007/s40264-014-0137-z

Background: Children are frequently prescribed medication `o-label', meaning there has not been sucient testing of the medication to determine its safety or eectiveness. The main reason this safety knowledge is lacking is due to ethical restrictions... Read More about Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs.

Practical detection of a definitive biomarker panel for Alzheimer's disease: comparisons between matched plasma and cerebrospinal fluid (2014)
Journal Article
Richens, J. L., Vere, K., Light, R. A., Soria, D., Garibaldi, J., Smith, A. D., …O’Shea, P. (2014). Practical detection of a definitive biomarker panel for Alzheimer's disease: comparisons between matched plasma and cerebrospinal fluid. International Journal of Molecular Epidemiology and Genetics, IJMEG, 5(2),

Previous mass spectrometry analysis of cerebrospinal fluid (CSF) has allowed the identification of a panel of molecular markers that are associated with Alzheimer’s disease (AD). The panel comprises Amyloid beta, Apolipoprotein E, Fibrinogen alpha ch... Read More about Practical detection of a definitive biomarker panel for Alzheimer's disease: comparisons between matched plasma and cerebrospinal fluid.

Comparison of algorithms that detect drug side effects using electronic healthcare databases (2013)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2013). Comparison of algorithms that detect drug side effects using electronic healthcare databases. Soft Computing, 17(12), https://doi.org/10.1007/s00500-013-1097-4

The electronic healthcare databases are starting to become more readily available and are thought to have excellent potential for generating adverse drug reaction signals. The Health Improvement Network (THIN) database is an electronic healthcare dat... Read More about Comparison of algorithms that detect drug side effects using electronic healthcare databases.

A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery (2013)
Journal Article
Reps, J. M., Garibaldi, J. M., Aickelin, U., Soria, D., Gibson, J. E., & Hubbard, R. B. (2014). A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE Journal of Biomedical and Health Informatics, 18(2), 537-547. https://doi.org/10.1109/JBHI.2013.2281505

Drugs are frequently prescribed to patients with the aim of improving each patient's medical state, but an unfortunate consequence of most prescription drugs is the occurrence of undesirable side effects. Side effects that occur in more than one in a... Read More about A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery.

A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means (2013)
Journal Article
Lai, D. T. C., Garibaldi, J. M., Soria, D., & Roadknight, C. M. (2014). A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means. Central European Journal of Operations Research, 22(3), 475-499. https://doi.org/10.1007/s10100-013-0318-3

Previously, a semi-manual method was used to identify six novel and clinically useful classes in the Nottingham Tenovus Breast Cancer dataset. 663 out of 1,076 patients were classified. The objectives of our work is three folds. Firstly, our primary... Read More about A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means.

A quantifier-based fuzzy classification system for breast cancer patients (2013)
Journal Article
Soria, D., Garibaldi, J. M., Green, A. R., Powe, D. G., Nolan, C. C., Lemetre, C., …Ellis, I. O. (2013). A quantifier-based fuzzy classification system for breast cancer patients. Artificial Intelligence in Medicine, 58(3), https://doi.org/10.1016/j.artmed.2013.04.006

Objectives:Recent studies of breast cancer data have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a range of different clustering techniques. Consensus between unsupervised classification algorithms ha... Read More about A quantifier-based fuzzy classification system for breast cancer patients.

Towards a more systematic approach to secure systems design and analysis (2013)
Journal Article
Miller, S., Appleby, S., Garibaldi, J. M., & Aickelin, U. (2013). Towards a more systematic approach to secure systems design and analysis. International Journal of Secure Software Engineering, 4(1), https://doi.org/10.4018/jsse.2013010102

The task of designing secure software systems is fraught with uncertainty, as data on uncommon attacks is limited, costs are difficult to estimate, and technology and tools are continually changing. Consequently, experts may interpret the security ri... Read More about Towards a more systematic approach to secure systems design and analysis.

Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data (2012)
Journal Article
Glaab, E., Bacardit, J., Garibaldi, J. M., & Krasnogor, N. (2012). Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. PLoS ONE, 7(7), Article e39932. https://doi.org/10.1371/journal.pone.0039932

Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new... Read More about Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

MysiRNA-designer: a workflow for efficient siRNA design (2011)
Journal Article
Mysara, M., Garibaldi, J. M., & ElHefnawi, M. (2011). MysiRNA-designer: a workflow for efficient siRNA design. PLoS ONE, 6(10), Article e25642. https://doi.org/10.1371/journal.pone.0025642

The design of small interfering RNA (siRNA) is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of si... Read More about MysiRNA-designer: a workflow for efficient siRNA design.

A "non-parametric" version of the naive Bayes classifier (2011)
Journal Article
Soria, D., Garibaldi, J. M., Ambrogi, F., Biganzoli, E. M., & Ellis, I. O. (2011). A "non-parametric" version of the naive Bayes classifier. Knowledge-Based Systems, 24(6), https://doi.org/10.1016/j.knosys.2011.02.014

Many algorithms have been proposed for the machine learning task of classication. One of the simplest methods, the naive Bayes classifyer, has often been found to give good performance despite the fact that its underlying assumptions (of independence... Read More about A "non-parametric" version of the naive Bayes classifier.

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients (2010)
Journal Article
Soria, D., Garibaldi, J. M., Ambrogi, F., Green, A. R., Powe, D., Rakha, E., …Ellis, I. O. (2010). A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients. Computers in Biology and Medicine, 40(3), https://doi.org/10.1016/j.compbiomed.2010.01.003

Single clustering methods have often been used to elucidate clusters in high dimensional medical data, even though reliance on a single algorithm is known to be problematic. In this paper, we present a methodology to determine a set of ‘core classes’... Read More about A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients.

Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms (2010)
Journal Article
Whitbrook, A., Aickelin, U., & Garibaldi, J. (2010). Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms. Evolutionary Intelligence, 3(3-4), https://doi.org/10.1007/s12065-010-0039-7

In mobile robotics, a solid test for adaptation is the ability of a control system to function not only in a diverse number of physical environments, but also on a number of different robotic platforms. This paper demonstrates that a set of behavi... Read More about Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms.

Cancer profiles by Affinity Propagation (2009)
Journal Article
Soria, D., Garibaldi, J. M., Ambrogi, F., Boracchi, P., Raimondi, E., & Biganzoli, E. M. (2009). Cancer profiles by Affinity Propagation. International Journal of Knowledge Engineering and Soft Data Paradigms, 1(3), https://doi.org/10.1504/IJKESDP.2009.028814

The Affinity Propagation algorithm is applied to various problems of breast and cutaneous tumours subtyping using traditional biologic markers. The algorithm provides a procedure to determine the number of profiles to be considered. Well know breast... Read More about Cancer profiles by Affinity Propagation.

The use of probabilistic systems to mimic the behaviour of idiotypic AIS robot controllers (2009)
Journal Article
Whitbrook, A., Aickelin, U., & Garibaldi, J. M. (2009). The use of probabilistic systems to mimic the behaviour of idiotypic AIS robot controllers. Journal of Systemics, Cybernetics and Informatics, 7(6),

Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to b... Read More about The use of probabilistic systems to mimic the behaviour of idiotypic AIS robot controllers.

Two-timescale learning using idiotypic behaviour mediation for a navigating mobile robot
Journal Article
Whitbrook, A., Aickelin, U., & Garibaldi, J. M. Two-timescale learning using idiotypic behaviour mediation for a navigating mobile robot. Applied Soft Computing, 10(3), https://doi.org/10.1016/j.asoc.2009.10.005

A combined short-term learning (STL) and long-term learning (LTL) approach to solving mobile-robot navigation problems is presented and tested in both the real and virtual domains. The LTL phase consists of rapid simulations that use a genetic algo... Read More about Two-timescale learning using idiotypic behaviour mediation for a navigating mobile robot.