Customized Structural Elicitation

Wilkerson, Rachel L.; Smith, Jim Q.

doi:10.1007/978-3-030-46474-5_4

Cited by 8 publications

(7 citation statements)

References 31 publications

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“…other care pathways a range of graphical models could be used, such as chain event graphs, dynamic Bayesian networks, multi-regression dynamic models, and flow graphs [Wilkerson and Smith, 2018]. This provides a rich area of potential research for those interested in graphical modelling.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…The translation of qualitative statements into formal graphical models such as Bayesian networks, in this paper the translation of the care pathway to an influence diagram, is an important area of current research. Recent work in this area includes Wilkerson and Smith [2018], Smith [2010], Korb and Nicholson [2009]. Here we adapt the approach given in Smith [2010].…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty representation for early phase clinical test evaluations: a case study

Graziadio,

Wilson

2020

Preprint

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In early clinical test evaluations the potential benefits of the introduction of a new technology into the healthcare system are assessed in the challenging situation of limited available empirical data. The aim of these evaluations is to provide additional evidence for the decision maker, who is typically a funder or the company developing the test, to evaluate which technologies should progress to the next stage of evaluation. In this paper we consider the evaluation of a diagnostic test for patients suffering from Chronic Obstructive Pulmonary Disease (COPD). We describe the use of graphical models, prior elicitation and uncertainty analysis to provide the required evidence to allow the test to progress to the next stage of evaluation. We specifically discuss inferring an influence diagram from a care pathway and conducting an elicitation exercise to allow specification of prior distributions over all model parameters. We describe the uncertainty analysis, via Monte Carlo simulation, which allowed us to demonstrate that the potential value of the test was robust to uncertainties. This paper provides a case study illustrating how a careful Bayesian analysis can be used to enhance early clinical test evaluations.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uncertainty representation for early phase clinical test evaluations: a case study

Graziadio,

Wilson

2020

Preprint

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“…These delegates were engaged in what can be called joint model building or soft elicitation (French, 2021; Wilkerson & Smith, 2021). First they were presented with the UK picture and then asked to express their beliefs about how this related specifically to Warwickshire.…”

Section: Idss: Uk Food Securitymentioning

confidence: 99%

A Decision Support System for Addressing Food Security in the United Kingdom

Barons

Fonseca

Davis

et al. 2021

Journal of the Royal Statistical Society Series A: Statistics in Society

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This paper presents an integrating decision support system (IDSS) for food security in the United Kingdom. In ever‐larger dynamic systems, such as the food system, it is increasingly difficult for decision makers (DMs) to effectively account for all the variables within the system that may influence the outcomes of interest under enactments of various candidate policies. Each of the influencing variables is likely, themselves, to be dynamic subsystems with expert domains supported by sophisticated probabilistic models. Recent increases in food poverty in the United Kingdom have raised the questions about the main drivers of food insecurity, how this may be changing over time and how evidence can be used in evaluating policy for decision support. In this context, an IDSS is proposed for household food security to allow DMs to compare several candidate policies which may affect the outcome of food insecurity at the household level.

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“…Therefore, it is not possible to ask domain experts to provide direct probabilistic inputs to the Bayesian model. What it is possible instead is to elicit structural information, which can take a wide range of forms depending on the domain (Wilkerson and Smith, 2019). These structural models can usually be represented by a graph (i.e., as a set of nodes and connecting arcs) which capture the fundamental entities and their relationships.…”

Section: Domain Knowledge Elicitationmentioning

confidence: 99%

Lexical semantic change for Ancient Greek and Latin

Perrone,

Hengchen,

Palma

et al. 2021

Preprint

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Change and its precondition, variation, are inherent in languages. Over time, new words enter the lexicon, others become obsolete, and existing words acquire new senses. Associating a word's correct meaning in its historical context is a central challenge in diachronic research. Historical corpora of classical languages, such as Ancient Greek and Latin, typically come with rich metadata, and existing models are limited by their inability to exploit contextual information beyond the document timestamp. While embedding-based methods feature among the current state of the art systems, they are lacking in the interpretative power. In contrast, Bayesian models provide explicit and interpretable representations of semantic change phenomena. In this chapter we build on GASC, a recent computational approach to semantic change based on a dynamic Bayesian mixture model. In this model, the evolution of word senses over time is based not only on distributional information of lexical nature, but also on text genres. We provide a systematic comparison of dynamic Bayesian mixture models for semantic change with state-of-the-art embedding-based models. On top of providing a full description of meaning change over time, we show that Bayesian mixture models are highly competitive approaches to detect binary semantic change in both Ancient Greek and Latin.

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Customized Structural Elicitation

Cited by 8 publications

References 31 publications

Uncertainty representation for early phase clinical test evaluations: a case study

Uncertainty representation for early phase clinical test evaluations: a case study

A Decision Support System for Addressing Food Security in the United Kingdom

Lexical semantic change for Ancient Greek and Latin

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