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William Marsh 0001
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- affiliation: Queen Mary University of London, United Kingdom
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2020 – today
- 2024
- [j23]Evangelia Kyrimi, Rebecca S. Stoner, Zane B. Perkins
, Erhan Pisirir, Jared M. Wohlgemut
Updating and recalibrating causal probabilistic models on a new target population. J. Biomed. Informatics 149: 104572 (2024) - [i3]Evangelia Kyrimi, Scott McLachlan, Jared M. Wohlgemut, Zane B. Perkins, David A. Lagnado, William Marsh, ExAIDSS Expert Group:
Explainable AI: Definition and attributes of a good explanation for health AI. CoRR abs/2409.15338 (2024) - 2023
- [c17]Erhan Pisirir, Jared M. Wohlgemut, Evangelia Kyrimi, Rebecca S. Stoner, Zane B. Perkins, Nigel R. M. Tai, D. William R. Marsh:
A Process for Evaluating Explanations for Transparent and Trustworthy AI Prediction Models. ICHI 2023: 388-397 - 2022
- [j22]Hakan Yücetürk
Reducing the question burden of patient reported outcome measures using Bayesian networks. J. Biomed. Informatics 135: 104230 (2022) - 2021
- [j21]Evangelia Kyrimi
Bayesian networks in healthcare: What is preventing their adoption? Artif. Intell. Medicine 116: 102079 (2021) - [j20]Haoyuan Zhang, D. William R. Marsh:
Managing infrastructure asset: Bayesian networks for inspection and maintenance decisions reasoning and planning. Reliab. Eng. Syst. Saf. 207: 107328 (2021) - [c16]Mariana R. Neves, Bridget J. Daley, Graham A. Hitman, Mohammed S. B. Huda, Scott McLachlan, Sarah Finer, William Marsh:
Causal Dynamic Bayesian Networks for the Management of Glucose Control in Gestational Diabetes. ICHI 2021: 31-40 - 2020
- [j19]Evangelia Kyrimi
An incremental explanation of inference in Bayesian networks for increasing model trustworthiness and supporting clinical decision making. Artif. Intell. Medicine 103: 101812 (2020) - [j18]Jane Waite
Difficulties with design: The challenges of teaching design in K-5 programming. Comput. Educ. 150: 103838 (2020) - [j17]Haoyuan Zhang
Multi-state deterioration prediction for infrastructure asset: Learning from uncertain data, knowledge and similar groups. Inf. Sci. 529: 197-213 (2020) - [j16]Evangelia Kyrimi
Medical idioms for clinical Bayesian network development. J. Biomed. Informatics 108: 103495 (2020) - [c15]Ali Fahmi
From Personalised Predictions to Targeted Advice: Improving Self-Management in Rheumatoid Arthritis. EFMI-STC 2020: 62-66 - [c14]Ali Fahmi
Causal Bayesian Networks for Medical Diagnosis: A Case Study in Rheumatoid Arthritis. ICHI 2020: 1-7 - [c13]Marta Wilk, D. William R. Marsh, Sarah De Freitas, John Prowle:
Predicting Length of Stay in Hospital Using Electronic Records Available at the Time of Admission. MIE 2020: 377-381 - [i2]Evangelia Kyrimi, Somayyeh Mossadegh, Nigel Tai, William Marsh:
An Incremental Explanation of Inference in Hybrid Bayesian Networks for Increasing Model Trustworthiness and Supporting Clinical Decision Making. CoRR abs/2003.02599 (2020) - [i1]Evangelia Kyrimi, Mariana Raniere Neves, Scott McLachlan, Martin Neil, William Marsh, Norman E. Fenton:
Medical idioms for clinical Bayesian network development. CoRR abs/2007.00364 (2020)
2010 – 2019
- 2019
- [c12]Mariana R. Neves, D. William R. Marsh
Modelling the Impact of AI for Clinical Decision Support. AIME 2019: 292-297 - 2018
- [j15]Jane Lisa Waite, Paul Curzon, William Marsh, Sue Sentance
Abstraction in action: K-5 teachers' uses of levels of abstraction, particularly the design level, in teaching programming. Int. J. Comput. Sci. Educ. Sch. 2(1): 14-40 (2018) - [c11]Barbaros Yet
Towards an Evidence-Based Decision Support Tool for Management of Musculoskeletal Conditions. EFMI-STC 2018: 175-179 - [c10]Jane Waite
Comparing K-5 teachers' reported use of design in teaching programming and planning in teaching writing. WiPSCE 2018: 4:1-4:10 - 2017
- [j14]Barbaros Yet
Clinical evidence framework for Bayesian networks. Knowl. Inf. Syst. 50(1): 117-143 (2017) - [c9]Jane Waite, Paul Curzon
K-5 Teachers' Uses of Levels of Abstraction Focusing on Design. WiPSCE 2017: 115-116 - 2016
- [j13]Anthony Costa Constantinou, Barbaros Yet
Value of information analysis for interventional and counterfactual Bayesian networks in forensic medical sciences. Artif. Intell. Medicine 66: 41-52 (2016) - [j12]Anthony Costa Constantinou, Norman E. Fenton
From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support. Artif. Intell. Medicine 67: 75-93 (2016) - [j11]Norman E. Fenton
How to model mutually exclusive events based on independent causal pathways in Bayesian network models. Knowl. Based Syst. 113: 39-50 (2016) - [c8]Evangelia Kyrimi, William Marsh:
A Progressive Explanation of Inference in 'Hybrid' Bayesian Networks for Supporting Clinical Decision Making. Probabilistic Graphical Models 2016: 275-286 - [c7]Jane Waite, Paul Curzon
Abstraction and common classroom activities. WiPSCE 2016: 112-113 - 2015
- [j10]Anthony Costa Constantinou, Mark Freestone
Causal inference for violence risk management and decision support in forensic psychiatry. Decis. Support Syst. 80: 42-55 (2015) - [j9]Anthony C. Constantinou, Mark Freestone
Risk assessment and risk management of violent reoffending among prisoners. Expert Syst. Appl. 42(21): 7511-7529 (2015) - 2014
- [j8]Barbaros Yet
Not just data: A method for improving prediction with knowledge. J. Biomed. Informatics 48: 28-37 (2014) - [j7]Barbaros Yet
Combining data and meta-analysis to build Bayesian networks for clinical decision support. J. Biomed. Informatics 52: 373-385 (2014) - [j6]Barbaros Yet
Compatible and incompatible abstractions in Bayesian networks. Knowl. Based Syst. 62: 84-97 (2014) - [c6]Barbaros Yet
Explicit Evidence for Prognostic Bayesian Network Models. MIE 2014: 53-57 - 2013
- [j5]Barbaros Yet
Decision support system for Warfarin therapy management using Bayesian networks. Decis. Support Syst. 55(2): 488-498 (2013) - [c5]Barbaros Yet, William Marsh, Zane Perkins, Nigel Tai, Norman E. Fenton:
Predicting Latent Variables with Knowledge and Data: A Case Study in Trauma Care. UAI Application Workshops 2013: 49
2000 – 2009
- 2008
- [j4]Norman E. Fenton
On the effectiveness of early life cycle defect prediction with Bayesian Nets. Empir. Softw. Eng. 13(5): 499-537 (2008) - 2007
- [j3]Norman E. Fenton, Martin Neil, William Marsh, Peter Stewart Hearty, David Marquez, Paul Krause, Rajat Mishra:
Predicting software defects in varying development lifecycles using Bayesian nets. Inf. Softw. Technol. 49(1): 32-43 (2007) - [c4]Norman E. Fenton
Project Data Incorporating Qualitative Factors for Improved Software Defect Prediction. PROMISE@ICSE 2007: 2 - [c3]William Marsh, George Bearfield:
Representing Parameterised Fault Trees Using Bayesian Networks. SAFECOMP 2007: 120-133 - 2005
- [c2]George Bearfield, William Marsh
Generalising Event Trees Using Bayesian Networks with a Case Study of Train Derailment. SAFECOMP 2005: 52-66 - 2004
- [c1]Norman E. Fenton, William Marsh
Making Resource Decisions for Software Projects. ICSE 2004: 397-406
1990 – 1999
- 1999
- [b1]David William Roff Marsh:
Program refinement using a universal law : language specification and prototype tool. University of Southampton, UK, 1999 - 1997
- [j2]William Marsh
Harmonisation of defence standards for safety-critical software. Microprocess. Microsystems 21(1): 41-47 (1997) - 1995
- [j1]Brian A. Wichmann, A. A. Canning, D. L. Clutterbuck, L. A. Winsborrow, N. J. Ward, D. William R. Marsh:
Industrial perspective on static analysis. Softw. Eng. J. 10(2): 69-75 (1995)
Coauthor Index
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last updated on 2024-10-16 20:31 CEST by the dblp team
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