Publications: Medical and health risk

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Daley B.J., Ni’Man M., Raniere Neves M., Huda M.S.B., Marsh W, Fenton N. E., Hitman G. A., and McLachlan S (2021) "mHealth Apps for Gestational Diabetes Mellitus that provide Clinical Decision Support or Artificial Intelligence: A Scoping Review", Diabetic Medicine http://dx.doi.org/10.1111/dme.14735

 

Hartmann M, Fenton NE and Dobson R (2021), "Using Bayesian networks to understand multiple sclerosis risk factor interactions", 37th Congress of the European Committee for Treatment and Research in Multiple Sclerosis, Oct 2021

 

Fenton, N. E., Neil, M., & McLachlan, G. S. (2021). Paradoxes in the reporting of Covid19 vaccine effectiveness
Why current studies (for or against vaccination) cannot be trusted and what we can do about it,

http://dx.doi.org/10.13140/RG.2.2.32655.30886

 

Neil, M and Fenton N E (2021), "Bayesian Hypothesis Testing and Hierarchical Modeling of Ivermectin Effectiveness", American Journal of Therapeutics, Vol 28, e577–e579, http://dx.doi.org/10.1097/MJT.0000000000001450

 

Neil, M and Fenton N E (2021), "Bayesian Hypothesis Testing and Hierarchical Modeling of Ivermectin Effectiveness", American Journal of Therapeutics, Vol 28, e577–e579

 

Neil, M and Fenton N E (2021), "Bayesian hypothesis testing and hierarchical modelling of ivermectin effectiveness in treating Covid-19" http://dx.doi.org/10.13140/RG.2.2.19703.75680

McLachlan,  S,  Osman, M,  Dube, K, Chiketero, P, Choi, Y, and Fenton N (2021) "Analysis of COVID-19 vaccine death reports from the Vaccine Adverse Events Reporting System (VAERS) Database",  http://dx.doi.org/10.13140/RG.2.2.26987.26402

 

Kyrimi, E., McLachlan, S., Dube, K., Neves, M. R., Fahmi, A., & Fenton, N. (2021). A comprehensive scoping review of Bayesian networks in healthcare: Past, present and future. Artificial Intelligence in Medicine, 117, 102108. https://doi.org/10.1016/J.ARTMED.2021.102108

 

Fenton, N. E., Neil, M., & McLachlan, G. S. (2021). What proportion of people with COVID-19 do not get symptoms? https://doi.org/10.13140/RG.2.2.33939.60968

Kyrimi E, Dube K, Fenton N E, Fahmi A, Raniere Neves M, Marsh W  & McLachlan, G. S. (2021), "Bayesian Networks in Healthcare: What is preventing their adoption?" Artificial Intelligence in Medicine, Vol 116, 102079,  https://doi.org/10.1016/j.artmed.2021.102079. PrePrint available here

 

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

McLachlan S, Kyrimi E, Dube K, Hitman G, Simmonds J and Fenton N E, “Towards Standardisation of Evidence-Based Clinical Care Process Specifications” (2020) 26 Health Informatics J. 25 (4), 2512-2538,  https://doi.org/10.1177/1460458220906069

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

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

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.

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

Dube, K., Mclachlan, S., Zanamwe, N., Kyrimi, E., Thomson, J. S., & Fenton, N. E (2020.). "Managing Knowledge in Computational Models for Global Food, Nutrition and Health Technologies."  2020 IEEE Global Humanitarian Technology Conference (GHTC) (GHTC 2020)  https://doi.org/10.1109/GHTC46280.2020.9342880 

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

Fenton, N. E., Osman, M., Neil, M., & McLachlan, S. (2020). Coronavirus: country comparisons are pointless unless we account for these biases in testing. The Conversation,  April 2, 2020  Spanish version: Coronavirus: las comparaciones entre países no tienen sentido a menos que tengamos en cuenta los sesgos en las pruebas.

Fenton, N. E., Osman M, Neil, M., & McLachlan, S. (2020). Improving the statistics and analysis of coronavirus by avoiding bias in testing and incorporating causal explanations for the data. pdf  

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., Dube K., Fenton N. (2020) Standardising Clinical Caremaps: Model, Method and Graphical Notation for Caremap Specification. In: Roque A. et al. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2019. Communications in Computer and Information Science, vol 1211. Springer, Cham  https://doi.org/10.1007/978-3-030-46970-2_21

Daley, B. J., Kyrimi, E., Dube, K., Fenton, N. E., Hitman, G. A., & McLachlan, S. (2020). Data Visualisation in Midwifery: The Challenge of Seeing what Datasets Hide. Studies in Health Technology and Informatics, 270, 1239–1240. https://doi.org/10.3233/SHTI200381

Mclachlan, S., Dube, K., Kyrimi, E., & Fenton, N. (2019). "LAGOS: learning health systems and how they can integrate with patient care". BMJ Health Care Inform, 26, 100037. https://doi.org/10.1136/bmjhci-2019-100037

Dube, K., McLachlan, S., Zanamwe, N., Kyrimi, E., Thomson, J., & Fenton, N. (2019). "Managing Knowledge Incorporated into Solution Models for Customisable Global Health Technologies". IEEE Global Humanitarian Technology Conference (GHTC), ISBN: 978-1-7281-1780-5/19 pages 303-310.

Zhang, H., Marsh, W. R., Fenton, N., & NEIL, M. (2019). "Realising the Potential for ML from Electronic Health Records". Proc. 1st International ‘Alan Turing’ Conference on Decision Support and Recommender Systems (DSRS-Turing 2019). London, UK. Accepted version (pdf)

McLachlan, Scott, Kudakwashe Dube, Thomas Gallagher, Jennifer A. Simmonds, and Norman Fenton. 2019. “Realistic Synthetic Data Generation: The ATEN Framework.” In , 497–523. Springer, Cham. https://doi.org/10.1007/978-3-030-29196-9_25

Daley, B., Hitman, G., Fenton, N.E., & McLachlan, S. (2019). "Assessment of the methodological quality of local clinical practice guidelines on the identification and management of gestational diabetes". BMJ Open, 9(6), e027285. https://doi.org/10.1136/bmjopen-2018-027285.  Full paper (pdf)

McLachlan, S., Dube, K., Johnson, O., Buchanan, D., Potts, H. W. W., Gallagher, T., Marsh, D.W.,  Fenton, N. E. (2019). "A Framework for Analysing Learning Health Systems: Are we removing the most impactful barriers?", Learning Health Systems, March 2019, Vol 3 (4), e10189 10.1002/lrh2.10189.  

McLachlan, S., Kyrimi, E., Dube, K., & Fenton, N. E.. (2019). "Clinical Caremap Development: How can caremaps standardise care when they are not standardised?" In HealthInf 13 Annual International Conference on Health Informatcis. Prague, Czech Republic. Feb 2019 Pre-publication version (pdf)

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

McLachlan, S., Potts, H., Dube, K., Buchanan, D., Lean, S., Gallagher, T., Johnson, O., Daley, B., Marsh, W., &  Fenton N.E. (2018), "The Heimdall Framework for Supporting Characterisation of Learning Health Systems",  BCS Journal of Innovation in Health Informatics, 25(2):77–87, http://dx.doi.org/10.14236/jhi.v25i2.996

McLachlan, S., Dube, K., Buchanan, D., Lean, S., Johnson, O., Potts, H., Gallagher, T,. Marsh, W.,  Fenton N.E. (2018). "Learning health systems: The research community awareness challenge". Journal of Innovation in Health Informatics, 25(1), 038-040 http://doi.org/10.14236/jhi.v25i1.981

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 NE, Neil M (2015), "Book Review: Malcom Kendrick “Doctoring Data: How to sort out medical advice from medical nonsense”. Download. Also http://dx.doi.org/10.13140/RG.2.1.4904.8804

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

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

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)

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
Preprint here.