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Computer Science and Engineering

Senior Lecturer

Reps, J.M., Garibaldi, J.M., Aickelin, U., Soria, D., Gibson, J.E. and Hubbard, R.B. 2014. Guest Editorial: Data Mining in Bioinformatics. IEEE Journal of Biomedical and Health Informatics. 18 (2), p. 483. doi:10.1109/JBHI.2014.2306988

Lai, D.T.C., Garibaldi, J.M., Soria, D. and Roadknight, C.M. 2014. A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-Means. Central European Journal of Operations Research. 22 (3), pp. 475-499. doi:10.1007/s10100-013-0318-3

Green, A.R., Soria, D., Stephen, J., Powe, D.G., Nolan, C.C., Kunkler, I., Thomas, J., Kerr, G.R., Jack, W., Cameron, D., Piper, T., Ball, G.R., Garibaldi, J.M., Rakha, E.A., Bartlett, J.M.S. and Ellis, I.O. 2016. Nottingham Prognostic Index Plus: Validation of a clinical decision making tool in breast cancer in an independent series. The Journal of Pathology: Clinical Research. 1 (2), pp. 32-40. doi:10.1002/cjp2.32

Richens, J.L., Vere, K.-A., Light, R.A., Soria, D., Garibaldi, J.M., Smith, A.D., Warden, D., Wilcock, G., Bajaj, N., Morgan, K. and O’Shea, P. 2014. Practical detection of a definitive biomarker panel for Alzheimer’s Disease; comparisons between plasma and cerebrospinal fluid. International Journal of Molecular Epidemiology and Genetics. 5 (2), pp. 53-70.

Reps, J.M., Aickelin, U., Garibaldi, J.M., Soria, D., Gibson, J.E. and Hubbard, R.B. 2014. Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs. Drug Safety. 37 (3), pp. 163-170. doi:10.1007/s40264-014-0137-z

Reps, J.M., Garibaldi, J.M., Aickelin, U., Soria, D., Gibson, J.E. and Hubbard, R.B. 2014. A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE Journal of Biomedical and Health Informatics. 18 (2), pp. 537-547. doi:10.1109/JBHI.2013.2281505

Rakha, E., Soria, D., Green, A.R., Lemetre, C., Powe, D.G., Nolan, C.C., Garibaldi, J.M., Ball, G.R. and Ellis, I.O. 2014. Nottingham Prognostic Index Plus (NPI+): A Modern Clinical Decision Making Tool in Breast Cancer. British Journal of Cancer. 110 (7), pp. 1688-1697. doi:10.1038/bjc.2014.120

Green, A.R., Soria, D., Powe, G., Nolan, C.C., Aleskandarany, N.M., Szász, M.A., Tőkés, A.M., Ball, G.R., Garibaldi, J.M., Rakha, E.A., Kulka, J. and Ellis, I.O. 2016. Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer. Breast Cancer Research and Treatment. 157 (1), pp. 65-75. doi:10.1007/s10549-016-3804-1

Agrawal, U., Soria, D. and Wagner, C. 2016. Cancer subtype identification pipeline: A classifusion approach. Evolutionary Computation (CEC), 2016 IEEE Congress on. 24 - 29 Jul 2016 IEEE . doi:10.1109/CEC.2016.7744150

Aleskandarany, M.A., Soria, D., Green, A.R., Nolan, C., Diez-Rodriguez, M., Ellis, I.O. and Rakha, E.A. 2015. Markers of Progression in Early-Stage Invasive Breast Cancer: a Predictive Immunohistochemical Panel Algorithm for Distant Recurrence Risk Stratification. Breast Cancer Research and Treatment. 151 (2), pp. 325-333. doi:10.1007/s10549-015-3406-3

Green, W.J.F., Ball, G., Hulman, G., Johnson, C., Van Schalwyk, G., Ratan, H.L., Soria, D., Garibaldi, J.M., Parkinson, R., Hulman, J., Rees, R. and Powe, D.G. 2016. KI67 and DLX2 predict increased risk of metastasis formation in prostate cancer–a targeted molecular approach. British Journal of Cancer. 115 (2), pp. 236-242. doi:10.1038/bjc.2016.169

Soria, D. and Garibaldi, J.M. 2016. Validation of a quantifier-based fuzzy classification system for breast cancer patients on external independent cohorts. IEEE International Conference on Machine Learning and Applications (ICMLA2016). Anaheim, California, USA 18 - 20 Dec 2016 IEEE . doi:10.1109/ICMLA.2016.0101

Figueredo, G.P., Agrawal, U., Mase, J.M.M., Mesgarpour, M., Wagner, C., Soria, D., Garibaldi, J.M., Siebers, P.O. and John, R.I. 2018. Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems. Advanced online publication. doi:10.1109/TITS.2018.2875343

Razak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A. and Soria, D. 2018. Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study. 2018 IEEE Symposium Series on Computational Intelligence. Bengaluru, India 18 - 21 Nov 2018 IEEE . doi:10.1109/SSCI.2018.8628924

Razak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A. and Soria, D. 2017. Interpretability indices for hierarchical fuzzy systems. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017). Naples, Italy 09 - 12 Jul 2017 IEEE . doi:10.1109/FUZZ-IEEE.2017.8015616

Agrawal, U., Pinar, A.J., Wagner, C., Havens, T.C., Soria, D. and Garibaldi, J.M. 2018. Comparison of Fuzzy Integral-Fuzzy Measure based Ensemble Algorithms with the State-of-the-art Ensemble Algorithms. Medina, J., Ojeda-Aciego, M., Verdegay, J.L., Perfilieva, I., Bouchon-Meunier, B. and Yager, R.R. (ed.) 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Cadiz, Spain 11 - 15 Jun 2018 Springer. doi:10.1007/978-3-319-91479-4

Salem, H., Caddeo, G., McFarlane, J., Patel, K., Cochrane, L., Soria, D., Henley, M. and Lund, J. 2018. A multicentre integration of a computer-led follow-up of prostate cancer is valid and safe. BJU international. 122 (3), pp. 418-426. doi:10.1111/bju.14157

Craze, M.L., Cheung, H., Jewa, N., Coimbra, N.D.M., Soria, D., El-Ansari, R., Aleskandarany, M.A., Cheng, K.W., Diez-Rodriguez, M., Nolan, C.C., Ellis, I.O., Rakha, E. and Green, A.R. 2018. MYC regulation of Glutamine-Proline regulatory axis is key in Luminal B breast cancer. British Journal of Cancer. 118 (2), pp. 258-265. doi:10.1038/bjc.2017.387

Liu, J., Xu, B., Zheng, C., Gong, Y., Garibaldi, J.M., Soria, D., Green, A., Ellis, I.O., Zou, W. and Qiu, G. 2019. An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA. IEEE Transactions on Medical Imaging. 38 (2), pp. 617-628. doi:10.1109/TMI.2018.2868333