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Number of items: 8. ArticleChen, Qi and Whitbrook, Amanda and 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 and 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 ItemRoadknight, Chris and Suryanarayanan, Durga and Aickelin, Uwe and 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 and Aickelin, Uwe and 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 and Aickelin, Uwe and Qiu, Guoping and 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 and Aickelin, Uwe and Ladas, Alex and Soria, Daniele and 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 (Unpublished) Roadknight, Chris and Aickelin, Uwe (2012) Extending a microsimulation of the Port of Dover.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 SectionRoadknight, Chris and 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 |
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