All Outputs (92)

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients (2010)
Journal Article

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.

Consensus clustering and fuzzy classification for breast cancer prognosis (2010)
Presentation / Conference Contribution
Garibaldi, J. M., Soria, D., & Rasmani, K. A. (2010). Consensus clustering and fuzzy classification for breast cancer prognosis.

A novel framework to elucidate core classes in a dataset (2010)
Presentation / Conference Contribution
Soria, D., & Garibaldi, J. M. (2010). A novel framework to elucidate core classes in a dataset.

In this paper we present an original framework to extract representative groups from a dataset, and we validate it over a novel case study. The framework specifies the application of different clustering algorithms, then several statistical and visu... Read More about A novel framework to elucidate core classes in a dataset.

Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms (2010)
Journal Article

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.

Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems (2009)
Presentation / Conference

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 be a... Read More about Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems.

The use of probabilistic systems to mimic the behaviour of idiotypic AIS robot controllers (2009)
Journal Article

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.

Cancer profiles by Affinity Propagation (2009)
Journal Article

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.

A comparison of three different methods for classification of breast cancer data (2008)
Presentation / Conference Contribution
Soria, D., Garibaldi, J. M., Biganzoli, E. M., & Ellis, I. O. (2008). A comparison of three different methods for classification of breast cancer data.

The classification of breast cancer patients is of great importance in cancer diagnosis. During the last few years, many algorithms have been proposed for this task. In this paper, we review different supervised machine learning techniques for classi... Read More about A comparison of three different methods for classification of breast cancer data.

Clustering breast cancer data by consensus of different validity indices
Presentation / Conference Contribution
Soria, D., Garibaldi, J. M., Ambrogi, F., Lisboa, P. J., Boracchi, P., & Biganzoli, E. M. Clustering breast cancer data by consensus of different validity indices.

Clustering algorithms will, in general, either partition a given data set into a pre-specified number of clusters or will produce a hierarchy of clusters. In this paper we analyse several different clustering techniques and apply them to a particular... Read More about Clustering breast cancer data by consensus of different validity indices.

An idiotypic immune network as a short-term learning architecture for mobile robots
Book Chapter

A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile robot navigation problems is presented and tested in both real and simulated environments. The LTL consists of rapid simulations that use a Genetic Algorith... Read More about An idiotypic immune network as a short-term learning architecture for mobile robots.

Two-timescale learning using idiotypic behaviour mediation for a navigating mobile robot
Journal Article

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.

The transfer of evolved artificial immune system behaviours between small and large scale robotic platforms
Book Chapter

This paper demonstrates that a set of behaviours evolved in simulation on a miniature robot (epuck) can be transferred to a much larger scale platform (a virtual Pioneer P3-DX) that also differs in shape, sensor type, sensor configuration and progra... Read More about The transfer of evolved artificial immune system behaviours between small and large scale robotic platforms.