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Bayesian networks in healthcare: Distribution by medical condition

Artificial intelligence in medicine, 2020-07, Vol.107, p.101912-101912, Article 101912

2020

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COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing

Journal of risk research, 2020-08, Vol.23 (7-8), p.862-865

2020

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An Extension to the Noisy-OR Function to Resolve the 'Explaining Away' Deficiency for Practical Bayesian Network Problems

IEEE transactions on knowledge and data engineering, 2019-12, Vol.31 (12), p.2441-2445

2019

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pi-football: A Bayesian network model for forecasting Association Football match outcomes

Knowledge-based systems, 2012-12, Vol.36, p.322-339

2012

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Explaining Away, Augmentation, and the Assumption of Independence

Frontiers in psychology, 2020-11, Vol.11, p.502751-502751

2020

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Propensities and Second Order Uncertainty: A Modified Taxi Cab Problem

Frontiers in psychology, 2020-10, Vol.11, p.503233-503233

2020

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Profiting from an inefficient association football gambling market: Prediction, risk and uncertainty using Bayesian networks

Knowledge-based systems, 2013-09, Vol.50, p.60-86

2013

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A Study of Using Bethe/Kikuchi Approximation for Learning Directed Graphic Models

IEEE access, 2021, Vol.9, p.125428-125438

2021

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Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe

Journal of clinical medicine, 2024-01, Vol.13 (2), p.334

2024

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Statistical Issues in Serial Killer Nurse Cases

Laws, 2022-10, Vol.11 (5), p.65

2022

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The Heimdall Framework for Supporting Characterisation of Learning Health Systems

BMJ health & care informatics, 2018-06, Vol.25 (2), p.77-87

2018

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Expected Value of Partial Perfect Information in Hybrid Models Using Dynamic Discretization

IEEE access, 2018-01, Vol.6, p.7802-7817

2018

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Towards smart-data: Improving predictive accuracy in long-term football team performance

Knowledge-based systems, 2017-05, Vol.124, p.93-104

2017

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Science and law: Improve statistics in court

Nature (London), 2011-11, Vol.479 (7371), p.36-37

Fenton, Norman

2011

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Learning Health Systems: The research community awareness challenge

BMJ health & care informatics, 2018, Vol.25 (1), p.981-40

2018

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A Bayesian network approach for cybersecurity risk assessment implementing and extending the FAIR model

Computers & security, 2020-02, Vol.89, p.101659, Article 101659

2020

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Current review and next steps for artificial intelligence in multiple sclerosis risk research

Computers in biology and medicine, 2021-05, Vol.132, p.104337-104337, Article 104337

2021

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Using Bayesian networks to guide the assessment of new evidence in an appeal case

Crime science, 2016-05, Vol.5 (1), p.9-9, Article 9

2016

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A hybrid Bayesian network for medical device risk assessment and management

Reliability engineering & system safety, 2024-01, Vol.241, p.109630, Article 109630

2024

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Improved reliability modeling using Bayesian networks and dynamic discretization

Reliability engineering & system safety, 2010-04, Vol.95 (4), p.412-425

2010

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Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved

Expert systems with applications, 2016-09, Vol.56, p.197-208

2016

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The Book of Why: The New Science of Cause and Effect, Judea Pearl, Dana Mackenzie, Basic Books (2018)

Artificial intelligence, 2020-07, Vol.284, p.1-3

2020

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Improve statistics in court: experts must agree a set of acceptable ways to assess and present forensic evidence

Nature (London), 2011-11, Vol.479 (7371), p.36

Fenton, Norman

2011

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Bayesian network approach to multinomial parameter learning using data and expert judgments

International journal of approximate reasoning, 2014-07, Vol.55 (5), p.1252-1268

2014

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WITHDRAWN: Improving predictive accuracy using smart-data: The case of football teams’ evolving performance

Knowledge-based systems, 2017-01

2017

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Bayesian networks in healthcare: Distribution by medical condition

COVID-19 infection and death rates: the need to incorporate causal explanations for the data and avoid bias in testing

An Extension to the Noisy-OR Function to Resolve the 'Explaining Away' Deficiency for Practical Bayesian Network Problems

pi-football: A Bayesian network model for forecasting Association Football match outcomes

Explaining Away, Augmentation, and the Assumption of Independence

Propensities and Second Order Uncertainty: A Modified Taxi Cab Problem

Profiting from an inefficient association football gambling market: Prediction, risk and uncertainty using Bayesian networks

A Study of Using Bethe/Kikuchi Approximation for Learning Directed Graphic Models

Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe

Statistical Issues in Serial Killer Nurse Cases

The Heimdall Framework for Supporting Characterisation of Learning Health Systems

Expected Value of Partial Perfect Information in Hybrid Models Using Dynamic Discretization

Towards smart-data: Improving predictive accuracy in long-term football team performance

Science and law: Improve statistics in court

Learning Health Systems: The research community awareness challenge

A Bayesian network approach for cybersecurity risk assessment implementing and extending the FAIR model

Current review and next steps for artificial intelligence in multiple sclerosis risk research

Using Bayesian networks to guide the assessment of new evidence in an appeal case

A hybrid Bayesian network for medical device risk assessment and management

Improved reliability modeling using Bayesian networks and dynamic discretization

Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved

The Book of Why: The New Science of Cause and Effect, Judea Pearl, Dana Mackenzie, Basic Books (2018)

Improve statistics in court: experts must agree a set of acceptable ways to assess and present forensic evidence

Bayesian network approach to multinomial parameter learning using data and expert judgments

WITHDRAWN: Improving predictive accuracy using smart-data: The case of football teams’ evolving performance

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