All Outputs (66)

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.

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.

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.

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.

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.