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Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. (2011)
Journal Article
REGNIER-COUDERT, O., MCCALL, J., LOTHIAN, R., LAM, T., MCCLINTON, S. and N'DOW, J. 2012. Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. Artificial intelligence in medicine [online], 55(1), pages 25-35. Available from: https://doi.org/10.1016/j.artmed.2011.11.003

Objectives: Prediction of prostate cancer pathological stage is an essential step in a patient's pathway. It determines the treatment that will be applied further. In current practice, urologists use the pathological stage predictions provided in Par... Read More about Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers..

Artificial reaction networks. (2011)
Presentation / Conference
GERRARD, C.E., MCCALL, J., COGHILL, G.M. and MACLEOD, C. 2011. Artificial reaction networks. Presented at the 11th UK workshop on computational intelligence (UKCI 2011), 7-9 September 2011, Manchester, UK.

In this paper we present a novel method of simulating cellular intelligence, the Artificial Reaction Network (ARN). The ARN can be described as a modular S-System, with some properties in common with other Systems Biology and AI techniques, including... Read More about Artificial reaction networks..

A sequence-length sensitive approach to learning biological grammars using inductive logic programming. (2011)
Thesis
MAMER, T. 2011. A sequence-length sensitive approach to learning biological grammars using inductive logic programming. Robert Gordon University, PhD thesis.

This thesis aims to investigate if the ideas behind compression principles, such as the Minimum Description Length, can help us to improve the process of learning biological grammars from protein sequences using Inductive Logic Programming (ILP). Con... Read More about A sequence-length sensitive approach to learning biological grammars using inductive logic programming..