• Login
• Admin

Article

Chen, Qi, Whitbrook, Amanda, Aickelin, Uwe and Roadknight, Chris (2014) Data classification using the Dempster-Shafer method. Journal of Experimental & Theoretical Artificial Intelligence . pp. 1-25. ISSN 0952-813X

Roadknight, Chris, Aickelin, Uwe and Sherman, Galina (2011) Validation of a microsimulation of the port of Dover. Journal of Computational Science, 3 (1-2). pp. 56-66. ISSN 1877-7503

Conference or Workshop Item

Roadknight, Chris, Suryanarayanan, Durga, Aickelin, Uwe, Scholefield, John and Durrant, Lindy (2015) An ensemble of machine learning and anti-learning methods for predicting tumour patient survival rates. In: 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA 2015), 19-21 Oct 2015, Paris, France.

Roadknight, Chris, Aickelin, Uwe, Scholefield, John and Durrant, Lindy (2013) Ensemble learning of colorectal cancer survival rates. In: IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) 2013, 15-17 July 2013, Milan, Italy.

Roadknight, Chris, Aickelin, Uwe, Qiu, Guoping, Scholefield, John and Durrant, Lindy (2012) Supervised learning and anti-learning of colorectal cancer classes and survival rates from cellular biology parameters. In: 2012 IEEE International Conference on Systems, Man and Cybernetics - SMC, 14-17 Oct 2012, Seoul, South Korea.

Roadknight, Chris, Aickelin, Uwe, Ladas, Alex, Soria, Daniele, Scholefield, John and Durrant, Lindy (2012) Biomarker clustering of colorectal cancer data to complement clinical classification. In: Federated Conference on Computer Science and Information Systems (FedCSIS), 9-12 Sept 2012, Wrocław, Poland. (Unpublished)

Roadknight, Chris and Aickelin, Uwe (2012) Extending a microsimulation of the Port of Dover. In: ORS SW12 Simulation Conference, 27-28 Mar 2012, Worcestershire, England.

Book Section

Roadknight, Chris, Zong, Guanyu and Rattadilok, Prapa (2019) Improving understanding of EEG measurements using transparent machine learning models. In: Health Information Science. Lecture Notes in Computer Science book series, 11837 . Springer Nature, Switzerland, pp. 134-142. ISBN 9783030329617