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Daniele Soria

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2020 – today

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2021
[j13]
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Mahmoud Aldraimli, Daniele Soria, Diana Grishchuck, Samuel Ingram, Robert J. Lyon, Anil Mistry, Jorge Oliveira, Robert Samuel, Leila E. A. Shelley, Sarah Osman, Miriam V. Dwek, David Azria, Jenny Chang-Claude, Sara Gutiérrez-Enríquez, Maria Carmen De Santis, Barry S. Rosenstein, Dirk De Ruysscher, Elena Sperk, R. Paul Symonds, Hilary Stobart, Ana Vega, Liv Veldeman, Adam Webb, Christopher J. Talbot, Catharine M. West, Tim Rattay, Thierry J. Chaussalet:
A data science approach for early-stage prediction of Patient's susceptibility to acute side effects of advanced radiotherapy. Comput. Biol. Medicine 135: 104624 (2021)
[j12]
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Hesham Salem, Daniele Soria, Jonathan N. Lund, Amir Awwad:
A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology. BMC Medical Informatics Decis. Mak. 21(1): 223 (2021)
[j11]
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Tajul Rosli Bin Razak, Jonathan M. Garibaldi, Christian Wagner, Amir Pourabdollah, Daniele Soria:
Toward a Framework for Capturing Interpretability of Hierarchical Fuzzy Systems - A Participatory Design Approach. IEEE Trans. Fuzzy Syst. 29(5): 1160-1172 (2021)
[c15]
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Aruna Duraisingam, Ramaswamy Palaniappan, Daniele Soria:
Attentional bias towards high and low caloric food on repeated visual food stimuli: An ERP study. EMBC 2021: 740-743

2010 – 2019

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2019
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Utkarsh Agrawal, Daniele Soria, Christian Wagner, Jonathan M. Garibaldi, Ian O. Ellis, John M. S. Bartlett, David Cameron, Emad A. Rakha, Andrew R. Green:
Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles. Artif. Intell. Medicine 97: 27-37 (2019)
[j9]
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Grazziela P. Figueredo, Utkarsh Agrawal, Jimiama M. M. Mase, Mohammad Mesgarpour, Christian Wagner, Daniele Soria, Jonathan M. Garibaldi, Peer-Olaf Siebers, Robert I. John:
Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Trans. Intell. Transp. Syst. 20(9): 3324-3336 (2019)
[j8]
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Jingxin Liu, Bolei Xu, Chi Zheng, Yuanhao Gong, Jon Garibaldi, Daniele Soria, Andrew R. Green, Ian O. Ellis, Wenbin Zou, Guoping Qiu:
An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA. IEEE Trans. Medical Imaging 38(2): 617-628 (2019)
[c14]
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Utkarsh Agrawal, Christian Wagner, Jonathan M. Garibaldi, Daniele Soria:
Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. FUZZ-IEEE 2019: 1-7
2018
[c13]
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Utkarsh Agrawal, Anthony J. Pinar, Christian Wagner, Timothy C. Havens, Daniele Soria, Jonathan M. Garibaldi:
Comparison of Fuzzy Integral-Fuzzy Measure Based Ensemble Algorithms with the State-of-the-Art Ensemble Algorithms. IPMU (1) 2018: 329-341
[c12]
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Tajul Rosli Bin Razak, Jonathan M. Garibaldi, Christian Wagner, Amir Pourabdollah, Daniele Soria:
Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study. SSCI 2018: 420-426
[i8]
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Jingxin Liu, Bolei Xu, Chi Zheng, Yuanhao Gong, Jon Garibaldi, Daniele Soria, Andrew R. Green, Ian O. Ellis, Wenbin Zou, Guoping Qiu:
An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer Tissue Microarray. CoRR abs/1801.06288 (2018)
2017
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T. R. Razak, Jonathan M. Garibaldi, Christian Wagner, Amir Pourabdollah, Daniele Soria:
Interpretability indices for hierarchical fuzzy systems. FUZZ-IEEE 2017: 1-6
2016
[c10]
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Utkarsh Agrawal, Daniele Soria, Christian Wagner:
Cancer subtype identification pipeline: A classifusion approach. CEC 2016: 2858-2865
[c9]
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Daniele Soria, Jonathan M. Garibaldi:
Validation of a Quantifier-Based Fuzzy Classification System for Breast Cancer Patients on External Independent Cohorts. ICMLA 2016: 576-581
2014
[j7]
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Daphne Teck Ching Lai, Jonathan M. Garibaldi, Daniele Soria, Christopher M. Roadknight:
A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-means. Central Eur. J. Oper. Res. 22(3): 475-499 (2014)
[j6]
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Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE J. Biomed. Health Informatics 18(2): 537-547 (2014)
[i7]
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Comparison of algorithms that detect drug side effects using electronic healthcare databases. CoRR abs/1409.0748 (2014)
[i6]
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
A Novel Semi-Supervised Algorithm for Rare Prescription Side Effect Discovery. CoRR abs/1409.0768 (2014)
[i5]
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs. CoRR abs/1409.0772 (2014)
[i4]
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Attributes for Causal Inference in Longitudinal Observational Databases. CoRR abs/1409.5774 (2014)
2013
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Daniele Soria, Jonathan M. Garibaldi, Andrew R. Green, Desmond G. Powe, Christopher C. Nolan, Christophe Lemetre, Graham R. Ball, Ian O. Ellis:
A quantifier-based fuzzy classification system for breast cancer patients. Artif. Intell. Medicine 58(3): 175-184 (2013)
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Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Comparison of algorithms that detect drug side effects using electronic healthcare databases. Soft Comput. 17(12): 2381-2397 (2013)
[c8]
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Attributes for causal inference in electronic healthcare databases. CBMS 2013: 548-549
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Discovering Sequential Patterns in a UK General Practice Database. CoRR abs/1307.1411 (2013)
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Comparing Data-mining Algorithms Developed for Longitudinal Observational Databases. CoRR abs/1307.1584 (2013)
[i1]
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Chris M. Roadknight, Uwe Aickelin, Alex Ladas, Daniele Soria, John Scholefield, Lindy Durrant:
Biomarker Clustering of Colorectal Cancer Data to Complement Clinical Classification. CoRR abs/1307.1601 (2013)
2012
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Discovering sequential patterns in a UK general practice database. BHI 2012: 960-963
[c6]
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Chris M. Roadknight, Uwe Aickelin, Alex Ladas, Daniele Soria, John Scholefield, Lindy Durrant:
Biomarker Clustering of Colorectal Cancer Data to Complement Clinical Classification. FedCSIS 2012: 187-191
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Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard:
Comparing data-mining algorithms developed for longitudinal observational databases. UKCI 2012: 1-8
2011
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Daniele Soria, Jonathan M. Garibaldi, Federico Ambrogi, Elia Biganzoli, Ian O. Ellis:
A 'non-parametric' version of the naive Bayes classifier. Knowl. Based Syst. 24(6): 775-784 (2011)
2010
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Daniele Soria, Jonathan M. Garibaldi, Federico Ambrogi, Andrew R. Green, Des Powe, Emad A. Rakha, R. Douglas Macmillan, Roger W. Blamey, Graham R. Ball, Paulo J. G. Lisboa, Terence A. Etchells, Patrizia Boracchi, Elia Biganzoli, Ian O. Ellis:
A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients. Comput. Biol. Medicine 40(3): 318-330 (2010)
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Daniele Soria, Jonathan M. Garibaldi:
A novel framework to elucidate core classes in a dataset. IEEE Congress on Evolutionary Computation 2010: 1-8
[c3]
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Jonathan M. Garibaldi, Daniele Soria, Khairul A. Rasmani:
Consensus Clustering And Fuzzy Classification For Breast Cancer Prognosis. ECMS 2010: 15-22

2000 – 2009

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2009
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Daniele Soria, Jonathan M. Garibaldi, Federico Ambrogi, Patrizia Boracchi, Elena Raimondi, Elia Biganzoli:
Cancer profiles by affinity propagation. Int. J. Knowl. Eng. Soft Data Paradigms 1(3): 195-215 (2009)
2008
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Daniele Soria, Jonathan M. Garibaldi, Elia Biganzoli, Ian O. Ellis:
A Comparison of Three Different Methods for Classification of Breast Cancer Data. ICMLA 2008: 619-624
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Federico Ambrogi, Elena Raimondi, Daniele Soria, Patrizia Boracchi, Elia Biganzoli:
Cancer Profiles by Affinity Propagation. ICMLA 2008: 650-655

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