Publications: Bayesian networks (applications)
Hunte, J., Neil, M., & Fenton, N. E. (2022). "A causal Bayesian network approach for consumer product safety and risk assessment" Journal of Safety Research 80, pp 198-214, https://doi.org/10.1016/j.jsr.2021.12.003
Hunte, J., Neil, M., & Fenton, N. E. (2021). A causal Bayesian network approach for consumer product safety and risk assessment: Research and Summary Report 2021/035. Office for Product Safety & Standards, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1018546/bayesian-networks-research-summary-report.pdf
Hartmann M, Fenton NE and Dobson R, “Current Review and Next Steps for Artificial Intelligence in Multiple Sclerosis Risk Research” (2021) Comput. Biol. Med. https://doi.org/10.1016/j.compbiomed.2021.104337 (also available here: Pre-print pdf)
Hartmann M, Fenton NE and Dobson R, “Recognizing and Adjusting for Paradoxes in Multiple Sclerosis Datasets Using Bayesian Networks” , submitted to ICHI 2021 IEEE International Conference on Healthcare Informatics (2021).
Fenton, N. E., McLachlan, S., Lucas, P., Dube, K., Hitman, G., Osman, M., Kyrimi, E. Neil, M. (2021). "A Bayesian network model for personalised COVID19 risk assessment and contact tracing" https://doi.org/10.1101/2020.07.15.20154286
Fenton, N. E. (2020) How to explain an increasing proportion of people testing positive for COVID if there is neither an increase in proportion of genuine cases nor increase in the false positive rate. https://doi.org/10.13140/RG.2.2.27902.20806
Collins, R., & Fenton, N. (2020). Bayesian network modelling for early diagnosis and prediction of Endometriosis. MedRxiv, 2020.11.04.20225946. https://doi.org/10.1101/2020.11.04.20225946
Fenton, N. E., McLachlan, S., Lucas, P., Dube, K., Hitman, G., Osman, M., Kyrimi, E. Neil, M. (2021). "A Bayesian network model for personalised COVID19 risk assessment and contact tracing" https://doi.org/10.1101/2020.07.15.20154286
Butcher, R., & Fenton, N. E. (2020). Extending the range of symptoms in a Bayesian Network for the Predictive Diagnosis of COVID-19, medRxiv https://doi.org/10.1101/2020.10.22.20217554
Prodhan, G., & Fenton, N. E. (2020). Extending the range of COVID-19 risk factors in a Bayesian network model for personalised risk assessment. medRxiv https://doi.org/10.1101/2020.10.20.20215814
Hunte, J., Fenton, N. E., & Neil, M. (2020). Product risk assessment: a Bayesian network approach. https://arxiv.org/abs/2010.06698
Osman, M., McLachlan, S., Fenton, N. E., Neil, M., Löfstedt, R., & Meder, B. (2020). "Learning from behavioural changes that fail". Trends in Cognitive Science, https://doi.org/10.1016/j.tics.2020.09.009 Blog post here. Accepted version (pdf).
Fenton N. E, Neil M, McLachlan S, Osman M (2020), "Misinterpreting statistical anomalies and risk assessment when analysing Covid-19 deaths by ethnicity", 10.13140/RG.2.2.18957.56807 Also here: preprint. Blog post here. To appear in Significance.
Fenton, N E., Neil, M., & Frazier, S. (2020). The role of collider bias in understanding statistics on racially biased policing. http://arxiv.org/abs/2007.08406
Fenton, N E. (2020). A Note on UK Covid19 death rates by religion: which groups are most at risk? http://arxiv.org/abs/2007.07083
Fenton, N. E., McLachlan, S., Lucas, P., Dube, K., Hitman, G., Osman, M., Kyrimi, E., Neil, M. (2020). "A privacy-preserving Bayesian network model for personalised COVID19 risk assessment and contact tracing". MedRxiv, 2020.07.15.20154286. https://doi.org/10.1101/2020.07.15.20154286
Kyrimi, E., Neves, M., Neil, M., Marsh, W., McLachlan, S., & Fenton, N. E. (2020). "Medical idioms for clinical Bayesian network development". Journal of Biomedical Informatics, Vol 108, 103495, https://doi.org/10.1016/j.jbi.2020.103495. Accepted version available here
Neil, M., Fenton, N E., Osman, M., & McLachlan, S. (2020). "Coronavirus: our study suggests more people have had it than previously estimated", The Conversation, 26 June 2020
Neil, M., Fenton, N.E, Osman, M., & McLachlan, S. (2020). "Bayesian Network Analysis of Covid-19 data reveals higher Infection Prevalence Rates and lower Fatality Rates than widely reported". Journal of Risk Research, 23 (7-8), 866-879 https://doi.org/10.1080/13669877.2020.1778771 . Preprint: MedRxiv, 2020.05.25.20112466. https://doi.org/10.1101/2020.05.25.20112466 Blog post here
Pilditch, T., Hahn, U., Fenton, N. E., & Lagnado, D. A. (2020). "Dependencies in evidential reports: The case for informational advantages". Cognition, Vol 204, 104343 https://doi.org/10.1016/j.cognition.2020.104343 Preprint (accepted version) here. Blog post here
Osman, M., Fenton, N. E. , McLachlan, S., Lucas, P., Dube, K., Hitman, G. A., Kyrimi, E, Neil, M, (2020)."The thorny problems of Covid-19 Contact Tracing Apps: The need for a holistic approach", Journal of Behavioral Economics for Policy, Vol. 4, 57-61. Published version. Also available here.
Dewitt, S., Fenton, N. E., & Liefgreen, AliceLagnado, D. A. (2020). Propensities and second order uncertainty: a modified taxi cab problem. Frontiers in Psychology, 11, 503233. https://doi.org/10.3389/fpsyg.2020.503233 Accepted version (pdf). Blog post here.
McLachlan, S., Dube, K., Hitman, G. A., Fenton, N. E., & Kyrimi, E. (2020). Bayesian networks in healthcare: Distribution by medical condition. Artificial Intelligence in Medicine, 107, 101912. https://doi.org/10.1016/J.ARTMED.2020.101912
McLachlan, S., Lucas, P., Dube, K., McLachlan, G. S., Hitman, G. A., Osman, M., Kyrimi, E, Neil, M, Fenton, N. E. (2020). "COVID-19 and contact tracing: literature review and additional analysis", submitted to BMC Public Health
Fenton, N E (2020), "Why most studies into COVID19 risk factors may be producing flawed conclusions-and how to fix the problem", http://arxiv.org/abs/2005.08608 Blog post here
McLachlan, S., Lucas, P., Dube, K., McLachlan, G. S., Hitman, G. A., Osman, M., Kyrimi, E, Neil, M, Fenton, N. E. (2020). "The fundamental limitations of COVID-19 contact tracing methods and how to resolve them with a Bayesian network approach". https://doi.org/10.13140/RG.2.2.27042.66243
McLachlan, S., Lucas, P., Dube, K., Hitman, G. A., Osman, M., Kyrimi, E., … Fenton, N. E. (2020). Bluetooth Smartphone Apps: Are they the most private and effective solution for COVID-19 contact tracing? http://arxiv.org/abs/2005.06621
Fenton, N. E., Neil, M., Osman, M., & McLachlan, S. (2020). "COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing". Journal of Risk Research, 1–4. https://doi.org/10.1080/13669877.2020.1756381
Fenton, N.E., Hitman, G. A., Neil, M., Osman, M., & McLachlan, S. (2020). Causal explanations, error rates, and human judgment biases missing from the COVID-19 narrative and statistics. PsyArXiv Preprints. https://doi.org/10.31234/OSF.IO/P39A4
Kyrimi, E, McLachlan, S, Dube, K, Neves M R, Fahmi,A, Fenton, N E, (2020) "A Comprehensive Scoping Review of Bayesian Networks in Healthcare: Past, Present and Future", arXiv:2002.08627
Kyrimi, E., McLachlan, S., Dube, K., & Fenton, N.E (2020). Bayesian Networks in Healthcare: the chasm between research enthusiasm and clinical adoption. MedRxiv, 2020.06.04.20122911. https://doi.org/10.1101/2020.06.04.20122911
McLachlan, S., Kyrimi, E., & Fenton, N. (2020). Public Authorities as Defendants: Using Bayesian Networks to determine the Likelihood of Success for Negligence claims in the wake of Oakden. http://arxiv.org/abs/2002.05664
Wang, J., Neil, M., & Fenton, N. E. (2020). "A Bayesian Network Approach for Cybersecurity Risk Assessment Implementing and Extending the FAIR Model". Computers and Security, Vol 89. DOI: 10.1016/j.cose.2019.101659
See also blog post.
Fenton, N. E.., Neil, M., Yet, B., & Lagnado, D. A. (2019). "Analyzing the Simonshaven Case using Bayesian Networks". Topics in Cognitive Science, 10.1111/tops.12417 . The published version can be read here: https://rdcu.be/bqYxp See also blog post
de Zoete, J., Fenton, N. E., Noguchi, T., & Lagnado, D. A. (2019). "Countering the ‘probabilistic paradoxes in legal reasoning’ with Bayesian networks". Science & Justice 59 (4), 367-379 10.1016/j.scijus.2019.03.003 The pre-publication version (pdf) The models See also blog post.
Neil, M., Fenton, N. E., Lagnado, D. A. & Gill, R. (2019), "Modelling competing legal arguments using Bayesian Model Comparison and Averaging". Artififical Intelligence and Law Vol 27, 403-430 . https://doi.org/10.1007/s10506-019-09250-3. The full published version can be read here. Pre-publication version (pdf)
Neil, M., Fenton, N. E., Osman, M., & Lagnado, D. A. (2019). Causality, the critical but often ignored component guiding us through a world of uncertainties in risk assessment. Journal of Risk Research, to 10.1080/13669877.2019.1606454. Pre-publication version (pdf).
Pilditch, T., Fenton, N. E., & Lagnado, D. A. (2019). "The zero-sum fallacy in evidence evaluation". Psychological Science Vol 30 (2), pp 250-260 http://doi.org/10.1177/0956797618818484 See also blog posting.
Fenton, N. E., (2018) "A Bayesian Network and Influence Diagram for a simple example of Drug Economics Decision Making", https://doi.org/10.13140/RG.2.2.33659.77600
Dewitt, S., Lagnado, D., & Fenton, N. E. (2018). "Updating Prior Beliefs Based on Ambiguous Evidence". In CogSci 2018 (pp. 306–311). Madison Wisconsin, 25-28 July 2018. ISBN: 978-0-9911967-8-4. see also Blog Post
Fenton N.E. (2018), "Handling Uncertain Priors in Basic Bayesian Reasoning", July 2018, https://doi.org/10.13140/RG.2.2.16066.89280
Fenton N.E.., & Neil, M. (2018). "How Bayesian Networks are pioneering
the ‘smart data’ revolution", Open Access Government, July 2018 pages 22-23. pdf version Also available here.
Fenton N.E., & Neil, M. (2018). "Improving Software Testing with Causal Modelling". In R. Kennet, F. Ruggeri, & F. Faltin (Eds.), Analytic Methods in Systems and Software Testing (pp. 27–63). John Wiley & Sons Ltd. https://doi.org/10.1002/9781119357056.ch2
Fenton N.E. (2018) "Evidence based decision making turns knowledge into power", EU Research 'Beyond the Horizon' Magazine, Spring 2018, pp 38-39. PDF version here.
Fenton N.E., & Neil, M. (2018). "Criminally Incompetent Academic Misinterpretation of Criminal Data - and how the Media Pushed the Fake News", Open Access Report 10.13140/RG.2.2.32052.55680. .
Fenton N.E., Lagnado D, de Zoete, J, "Modeling complex legal cases as a Bayesian network (BN) using idioms and sensitivity analysis with the Collins case as a complete example", ICFIS2017 (10th International Conference on Forensic Inference and Statistics), Mineapolis, USA, Sept 2017. 10.13140/RG.2.2.35414.55360
de Zoete, J, Fenton N.E. ,"Automatic Generation of Bayesian networks in Forensic Science", ICFIS2017 (10th International Conference on Forensic Inference and Statistics), Mineapolis, USA, Sept 2017, 10.13140/RG.2.2.17798.47689
Constantinou, A., & Fenton, N.E (2017). "The future of the London Buy-To-Let property market: Simulation with Temporal Bayesian Networks". PLoS ONE 12(6): e0179297 doi.org/10.1371/journal.pone.0179297 (open access) 27 June 2017
Neil, M. & Fenton, N.E. "Risk Management Using Bayesian Networks" in Wiley StatsRef: Statistics Reference Online 1–6 (John Wiley & Sons, Ltd, 2017). doi:10.1002/9781118445112.stat07943
Fenton, N.E., Constantinou, A., & Neil, M. (2017). "Combining judgments with messy data to build Bayesian Network models for improved intelligence analysis and decision support". In Subjective Probability, Utility and Decision Making Conference (SPUDM 17). Haifa, Israel.
Constantinou, A. C. and Fenton, N.E. (2017). Towards Smart-Data: Improving predictive accuracy in long-term football team performance. Knowledge-Based Systems, Vol 124, pages 93-104, http://dx.doi.org/10.1016/j.knosys.2017.03.005 Open access pre-publication version. See blog posting.
Dementiev E and Fenton N E, "Bayesian Torrent Classification by File Name and Size Only", International Conference on Probabilistic Graphical Models, Lugano, Switzerland, 06 Sep 2016 - 09 Sep 2016. Journal of Machine Learning Research. 52: 136-147. 09 Sep 2016. Published version.
Constantinou A and Fenton NE. "Improving predictive accuracy using Smart-Data rather than Big-Data: A case study of soccer teams' evolving performance" In Proceedings of the 13th UAI Bayesian Modeling Applications Workshop (BMAW 2016), 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), New York City, USA, June 25-29, 2016. Published version
Yet, B., Constantinou, A. C., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2016). A Bayesian Network Framework for Project Cost, Benefit and Risk Analysis with an Agricultural Development Case Study. Expert Systems with Applications, Volume 60 Oct 2016, pages 141-155 http://dx.doi.org/10.1016/j.eswa.2016.05.005 pre-publication version here See also blog posting
Smit, N. M., Lagnado, D. A., Morgan, R. M., & Fenton, N. E. (2016). "Using Bayesian networks to guide the assessment of new evidence in an appeal case". Crime Science, 2016, 5: 9, DOI 10.1186/s40163-016-0057-6 (open source). Published version pdf. See also blog posting
Constantinou, A. C., Fenton, N., Marsh, W., & Radlinski, L. (2016). "From complex questionnaire and interviewing data to intelligent Bayesian Network models for medical decision support", Artificial Intelligence in Medicine, 2016. Vol 67 pages 75-93. http://dx.doi.org/10.1016/j.artmed.2016.01.002, Pre-publication version here.
Constantinou, A. C., Yet, B., Fenton, N., Neil, M., & Marsh, W. (2016). Value of Information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences. Artificial Intelligence in Medicine. 66, pp 41-52 doi:10.1016/j.artmed.2015.09.002 Pre-publication version here.
Fenton, N.E., 2015. Debunking report that claims gender diverse executive Boards outperform male-only Boards, Queen Mary University of London, Report Number BK_TR_05_15, http://dx.doi.org/10.13140/RG.2.1.1221.4160/1
Fenton NE, "Handling Anonymous Witness Evidence using Bayesian Network idioms" Working paper.
Shepherd, K., Hubbard, D., Fenton, N. E., Claxton, K., Luedeling, E., de Leeuw, J., (2015) "Development goals should enable decision-making", Nature 532: 152-154, 9 July 2015, http://dx.doi.org/10.1038/523152a
Constantinou, A., Freestone M., Marsh, W., Fenton, N. E. , Coid, J. (2015) "Risk assessment and risk management of violent reoffending among prisoners", Expert Systems With Applications 42 (21), 7511-7529. Pre-publication draft here. Published version: http://dx.doi.org/10.1016/j.eswa.2015.05.025
Yet, B., Constantinour A., Fenton N. E., Neil M., Leudeling E., Shepherd, K., "Project Cost, Benefit and Risk Analysis using Bayesian Networks", Bayesian Applications Workshop, 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, 16 July 2015. Published as abstract.
Fenton, N. E, "Moving from big data and machine learning to smart data and causal modelling: a simple example from consumer research and marketing", March 2015. DOI: http://dx.doi.org/10.13140/RG.2.1.3292.8166
de Zoete, J, Sjerps, M, Lagnado,D, Fenton, N.E. (2015), "Modelling crime linkage with Bayesian Networks" Law, Science & Justice, 55(3), 209-217. http://doi:10.1016/j.scijus.2014.11.005 Pre-publication draft here. Slides from ICFIS 2014 Presentation
Lin, P., Neil, M. & Fenton, N. E. Risk Aggregation in the presence of Discrete Causally Connected Random Variables. Ann. Actuar. Sci. 8, 298–31 (2014). http://dx.doi.org/10.1017/S1748499514000098. Pre-publication draft here.
Fenton, N. E., & Neil, M. (2014). "Decision Support Software for Probabilistic Risk Assessment Using Bayesian Networks". IEEE Software, 31(2), 21–26. http://dx.doi.org/10.1109/MS.2014.32 Author's final version here.
Constantinou, A. C., Fenton, N. E., & Pollock, L. (2014). Bayesian networks for unbiased assessment of referee bias in Association Football. Psychology of Sport & Exercise, 15(5) 538–547, http://dx.doi.org/10.1016/j.psychsport.2014.05.009. Pre-publication draft here.
Fenton, N. E., Neil, M., & Hsu, A. (2014). "Calculating and understanding the value of any type of match evidence when there are potential testing errors". Artificial Intelligence and Law, 22. 1-28 . http://dx.doi.org/10.1007/s10506-013-9147-x Pre-publication draft here. Note that Table 2 is wrong in the published version. See change.
Fenton, N. E.(2014) "A Bayesian Network for a simple example of Drug Economics Decision Making", working paper DOI: http://10.13140/RG.2.1.1130.1281
Fenton, N. E., Neil, M. (2014) "Who put Bella in the wych elm? A Bayesian analysis of a 70 year-old mystery", Technical Report produced for BBC Radio 4 Programme Punt-PI, 2 August 2014
Lin, P., Neil, M., & Fenton, N. E. (2014). "Risk Aggregation in the presence of Discrete Causally Connected Random Variables". Annals of Actuarial Science, 8(2), 298-319, http://dx.doi.org/10.1017/S1748499514000098. Pre-publication draft here.
Fenton, N. E., D. Berger, D. Lagnado, M. Neil and A. Hsu, (2014). "When ‘neutral’ evidence still has probative value (with implications from the Barry George Case)", Science and Justice, 54(4), 274-287 http://dx.doi.org/10.1016/j.scijus.2013.07.002 (pre-publication draft here)
Yet, B., Perkins Z., Fenton, N.E., Tai, N., Marsh, W., (2014) "Not Just Data: A Method for Improving Prediction with Knowledge", Journal of Biomedical Informatics, Vol 48, 28-37 http://dx.doi.org/10.1016/j.jbi.2013.10.012 (see here for details of model)
Constantinou, Anthony C. & Fenton, N. E. (2013). Profiting from arbitrage and odds biases of the European football gambling market, Journal of Gambling Business and Economics, Vol. 7(2), 41-70. Journal link here. Pre-publication draft here.
Constantinou, A., N. E. Fenton and M. Neil (2013) "Profiting from an Inefficient Association Football Gambling Market: Prediction, Risk and Uncertainty Using Bayesian Networks". Knowledge-Based Systems. Vol 50, 60-86 http://dx.doi.org/10.1016/j.knosys.2013.05.008
Fenton, N. E., D. Lagnado and M. Neil (2013). "A General Structure for Legal Arguments Using Bayesian Networks." Cognitive Science 37, 61-102 http://dx.doi.org/10.1111/cogs.12004. Pre-publication version here.
Constantinou, A. C. and N. E. Fenton (2013). "Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries." Journal of Quantitative Analysis in Sports 9(1): 37-50. Pre-publication version http://dx.doi.org/10.1515/jqas-2012-0036
Lagnado, D. A., N. E. Fenton and M. Neil (2013). "Legal idioms: a framework for evidential reasoning." Argument and Computation, 2013, 4(1), 46-63 http://dx.doi.org/10.1080/19462166.2012.682656
Zhou, Y., Fenton, N. E., Neil, M., & Zhu, C. (2013). Incorporating Expert Judgement into Bayesian Network Machine Learning. In 23rd International Joint Conference on Artificial Intelligence (IJCAI2013) (pp. 3249–3250). China: AAAI Press.
Yun Zhou, Norman Fenton, Martin Neil, Cheng Zhu, "Incorporating Expert Judgement into Bayesian Network Machine Learning", 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), 2013
Constantinou, A., N. E. Fenton and M. Neil (2012). ""pi-football: A Bayesian network model for forecasting Association Football match outcomes." Knowledge Based Systems, 36, 322-339. Pre-publication version. http://dx.doi.org/10.1016/j.knosys.2012.07.008
Fenton, N.E. and Neil, M. (2011), 'Avoiding Legal Fallacies in Practice Using Bayesian Networks', Australian Journal of Legal Philosophy 36, 114-151, 2011 ISSN 1440-4982 (extended preprint draft here).
Fenton, N.E. and Neil, M., 'The use of Bayes and causal modelling in decision making, uncertainty and risk', UPGRADE, the Journal of CEPIS (Council of European Professional Informatics Societies), 12(5), 10-21, 2011. Published verion here.
Yet, B., Perkins Z.,Marsh, W., Fenton, N.E., "Towards a Method of Building Causal Bayesian Networks for Prognostic Decision Support", ProBioMed 11, Bled, Slovenia, July 2011
Fenton, N. and Neil, M. (2010). "Comparing risks of alternative medical diagnosis using Bayesian arguments." Journal of Biomedical Informatics, 43: 485-495, http://dx.doi.org/10.1016/j.jbi.2010.02.004
Neil, M., Marquez, D. and Fenton, N. E. (2010). "Improved Reliability Modeling using Bayesian Networks and Dynamic Discretization." Reliability Engineering & System Safety, 95(4), 412-425, http://dx.doi.org/10.1016/j.ress.2009.11.012
Fenton, N. E., Hearty, P., Neil, M. and Radliński, Ł. (2009). "Software Project and Quality Modelling Using Bayesian Networks Artificial Intelligence" in Applications for Improved Software Engineering Development: New Prospects. (Eds Meziane, F. and Vadera, S. Hershey), New York, USA, IGI Global: Chapter 1,1-25.
Fineman, M., Radlinski, L. and Fenton, N. E. (2009). Modelling Project Trade-off Using Bayesian Networks. IEEE Int. Conf. Computational Intelligence and Software Engineering. Wuhan, China, IEEE Computer Society. http://dx.doi.org/10.1109/CISE.2009.5364789
Fineman, M. and Fenton, N. E. (2009). Quantifying Risks Using Bayesian Networks. IASTED Int. Conf. Advances in Management Science and Risk Assessment (MSI 2009). Beijing, China, IASTED. 662-219, pp 1227-1233
Radliński, Ł. & Fenton, N., 2009. Causal Risk Framework for Software Projects. In Z. Wilimowska et al. Information Systems Architecture and Technology. IT Technologies in Knowledge Oriented Management Process. Wrocław, Poland: Oficyna Wydawnicza Politechniki Wrocławskiej, pp. 49-59.
Hearty, P., Fenton, N., Marquez, D., and Neil, M., Predicting Project Velocity in XP using a Learning Dynamic Bayesian Network Model. IEEE Trans Software Eng, 2009. 35(1): 124-137.
Radliński Ł , Fenton N E, Neil M, Zarządzaniu II w, "A Learning Bayesian Net for Predicting Number of Software Defects Found in a Sequence of Testing", Polish Journal of Environmental Studies 17 (3B), 359-364, 2008
Fenton, N.E. and Neil, M., Avoiding Legal Fallacies in Practice Using Bayesian Networks (Seventh International Conference on Forensic Inference and Statistics. 2008: Lausanne, Switzerland).
Fenton, N.E., Neil, M., and Marquez, D., Using Bayesian Networks to Predict Software Defects and Reliability. Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, 2008. 222(O4): p. 701-712, 10.1243/1748006XJRR161
Fenton, N.E., Neil, M., Marsh, W., Hearty, P., Radlinski, L., and Krause, P., On the effectiveness of early life cycle defect prediction with Bayesian Nets. Empirical Software Engineering, 2008. 13: p. 499-537.
Marquez, D., Neil, M., and Fenton, N., Solving Dynamic Fault Trees using a New Hybrid Bayesian Network Inference Algorithm, in 16th Mediterranean Conference on Control and Automation (MOD 08). 2008: Ajaccio, Corsica, France, pp 609-614, http://dx.doi.org/10.1109/MED.2008.4602222
Marquez, D., Neil, M., and Fenton, N.E., Reliability Modelling Using Hybrid Bayesian Networks, in ISBIS-2008 International Symposium on Business and Industrial Statistics. 2008: Prague, Czech Republic.
Neil, M., Marquez, D., and Fenton, N., Using Bayesian Networks to Model the Operational Risk to Information Technology Infrastructure in Financial Institutions. Journal of Financial Transformation, 2008. 22: p. 131-138.
Neil, M., Tailor, M., Marquez, D., Fenton, N.E., and Hearty, P., Modelling dependable systems using hybrid Bayesian networks. Reliability Engineering and System Safety, 2008. 93(7): p. 933-939.
Radliński, Ł., Fenton, N.E., Neil, M., and Marquez, D., Improved Decision-Making for Software Managers Using Bayesian Networks, in 11th IASTED Int. Conf. Software Engineering and Applications (SEA). 2007: Cambridge, MA, USA p. 13–19.
Marquez D, Neil M, Fenton NE, "Improved Dynamic Fault Tree modelling using Bayesian Networks", The 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2007, Edinburgh 2007
Radliński, Ł., Fenton, N.E., Neil, M., and Marquez, D., Modelling Prior Productivity and Defect Rates in a Causal Model for Software Project Risk Assessment. Polish Journal of Environmental Studies, 2007. 16(4A): p. 256-260
Fenton NE, Neil M, Marsh W, Hearty P, Krause P, Radliński Ł. , "Project Data Incorporating Qualitative Factors for Improved Software Defect Prediction, ICSE PROMISE 2007 The dataset and model associated with this paper can be found here.
Neil, M., Fenton, N., and Marquez, D., Using Bayesian Networks and Simulation for Data Fusion and Risk Analysis, in NATO Science for Peace and Security Series: Information and Communication Security, Skanata and Byrd, D.M., Editors. 2007, IOS Press, Nieuwe Hemweg 6B, 1013 BG Amsterdam, The Netherlands
Fenton NE, Neil M, Hearty P, Marsh W, Marquez D, Krause P, Mishra R, "Predicting Software Defects in Varying Development Lifecycles using Bayesian Nets", Information & Software Technology, Vol 49, pp 32-43, Jan 2007
Norman Fenton, Łukasz Radliński, Martin Neil "Improved Bayesian Networks for Software Project Risk Assessment Using Dynamic Discretisation, IFIP Conference Software Engineering Techniques (SET 2006), Warsaw, Poland, 17-20 Oct 2006, in "Software Engineering Techniques: Design for Quality ", pp 139-148, Springer Boston, ISBN 978-0-387-39387-2, http://dx.doi.org/10.1007/978-0-387-39388-9_14
Joseph A, Fenton NE, Neil M, "Predicting football results using Bayesian Nets and other Machine Learning Techniques", Knowledge Based Systems, Volume 19, Issue 7, Pages 544-553, Nov 2006 Old Version with additional data is here.
Neil M, Marquez D, Fenton N, Tailor M, Hearty P, "Modelling Dependable Systems using Hybrid Bayesian Networks", First International Conference on Availability, Reliability and Security (ARES 2006), 20-22 April 2006, Vienna, Austria
Hearty P, Fenton NE, Neil M, Cates P, "Automated population of causal models for improved software risk assessment", 20th IEEE/ACM International Conference on Automated Software Engineering, Long Beach, California, USA, November 7-11, 2005, pp 433-435, ACM Press, ISBN: 1-59593-993-4
Fenton NE and Neil M, ''A Critique of Software Defect Prediction Models'', in Machine Learning Applications in Software Engineering (eds: Zhang D, Tsai JJP), pp 72-86, ISBN 981-256-094-7, World Scientific Publishing Co, 2005
Fenton NE, Marsh W, Neil M, Cates P, Forey S, Tailor T, "Making Resource Decisions for Software Projects", 26th International Conference on Software Engineering (ICSE 2004), May 2004, Edinburgh, United Kingdom. IEEE Computer Society 2004, ISBN 0-7695-2163-0, pp. 397-406
Neil M, Krause P, Fenton NE, "Software Quality Prediction Using Bayesian Networks" in Software Engineering with Computational Intelligence, (Ed Khoshgoftaar TM), Kluwer, ISBN 1-4020-7427-1, Chapter 6, 2003
Neil M, Fenton N, Forey S and Harris R. "Assessing Vehicle Reliability using Bayesian Networks" in Global Vehicle Reliability, Edited by J. E. Strutt and P.L. Hall. Professional Engineering Publishing, 25-42, 2003.
Fenton N, Krause P, Neil M, "Probabilistic Modelling for Software Quality Control", Journal of Applied Non-Classical Logics 12(2), 173-188, 2002
Fenton N, Krause P, Neil M, "Software Metrics: Uncertainty and Causal Modelling",. EuroSPI conference, Limerick Institute of Technology, Limerick, 10th-12th October 2001.
Fenton N, Krause P, Neil M, "Probabilistic Modelling for Software Quality Control", Sixth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty September 19-21, 2001, Toulouse, France.
Fenton NE and Neil M, ''Bayesian belief nets: a causal model for predicting defect rates and resource requirements'', Software Testing and Quality Engineering 2(1), 48-53, 2000
Littlewood B, Strigini L, Wright D, Fenton NE, Neil M, "Bayesian Belief Networks for Safety Assessment of Computer-based Systems", in System Performance Evaluation Methodologies and Applications (Ed: Gelenbe E), CRC Press, Boca Raton ISBN 0-8493-2357-6, pp 349-364, 2000
Fenton NE, Littlewood B, Neil M, Strigini L, Sutcliffe A, Wright D, ''Assessing Dependability of Safety Critical Systems using Diverse Evidence'', IEE Proceedings Software Engineering, 145(1), 35-39, 1998.
Neil M and Fenton NE, Predicting software quality using Bayesian belief networks, Proc 21st Annual Software Eng Workshop, NASA Goddard Space Flight Centre, 217-230, Dec, 1996.
Neil M, Littlewood B, Fenton NE, Applying Bayesian belief networks to systems dependability assessment, in Proceedings of 4th Safety Critical Systems Symposium, Springer Verlag, 71-93, 1996.