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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. https://doi.org/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. https://doi.org/10.1007/s10100-013-0318-3

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. https://doi.org/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. https://doi.org/10.1109/JBHI.2013.2281505

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. https://doi.org/10.1002/cjp2.32

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 . https://doi.org/10.1109/CEC.2016.7744150

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.

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. https://doi.org/10.1038/bjc.2014.120

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. https://doi.org/10.1007/s10549-015-3406-3

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. https://doi.org/10.1007/s10549-016-3804-1

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. https://doi.org/10.1038/bjc.2016.169

Aldraimli, M., Soria, D., Parkinson, J., Whitcher, B., Thomas, E.L., Bell, J.D., Chaussalet, T.J. and Dwek, M. 2019. Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases. MEDICON 2019: XV Mediterranean Conference on Medical and Biological Engineering and Computing. Coimbra, Portugal 26 - 28 Sep 2019 Springer. https://doi.org/10.1007/978-3-030-31635-8_81

Agrawal, U., Wagner, C., Garibaldi, J.M. and Soria, D. 2019. Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. International Conference on Fuzzy Systems (FUZZ-IEEE 2019). 23 - 26 Jun 2019 IEEE . https://doi.org/10.1109/FUZZ-IEEE.2019.8858821

Agrawal, U., Soria, D., Wagner, C., Garibaldi, J.M., Ellis, I.O., Bartlett, J.M.S., Cameron, D., Rakha, E.A. and Green, A.R. 2019. Combining Clustering and Classification Ensembles: A Novel Pipeline to Identify Breast Cancer Profiles. Artificial Intelligence in Medicine. 97, pp. 27-37. https://doi.org/10.1016/j.artmed.2019.05.002

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. 2019. Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems. 20 (9), pp. 3324-3336. https://doi.org/10.1109/TITS.2018.2875343

Vedhara, K., Dawe, K., Miles, J.N.V., Wetherell, M.A., Cullum, N., Dayan, C., Drake, N., Price, P., Tarlton, J., Weinman, J., Day, A., Campbell, R., Reps, J. and Soria, D. 2016. Illness Beliefs Predict Mortality in Patients with Diabetic Foot Ulcers. PLoS ONE. 11 (4) e0153315. https://doi.org/10.1371/journal.pone.0153315

El Ansari, R., Craze, M.L., Alfarsi, L., Soria, D., Diez-Rodriguez, M., Nolan, C.C., Ellis, I.O., Rakha, E.A. and Green, A.R. 2019. The combined expression of solute carriers is associated with a poor prognosis in highly proliferative ER+ breast cancer. Breast Cancer Research and Treatment. 175 (1), pp. 27-38. https://doi.org/10.1007/s10549-018-05111-w

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. https://doi.org/10.1109/TMI.2018.2868333

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. https://doi.org/10.1038/bjc.2017.387

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 . https://doi.org/10.1109/ICMLA.2016.0101