46 citations · 52 across the 6 of their papers we have counts for
6 papers
The BEAT-CF Causal Model: A model for guiding the design of trials and observational analyses of cystic fibrosis exacerbations
Steven Mascaro, Owen Woodberry, Charlie McLeod +5
Loss of lung function in cystic fibrosis (CF) occurs progressively, punctuated by acute pulmonary exacerbations (PEx) in which abrupt declines in lung function are not fully recove…
Comparing verbal, visual and combined explanations for Bayesian Network inferences
Erik P. Nyberg, Steven Mascaro, Ingrid Zukerman +3
Bayesian Networks (BNs) are an important tool for assisting probabilistic reasoning, but despite being considered transparent models, people have trouble understanding them. Furthe…
Causal knowledge engineering: A case study from COVID-19
Steven Mascaro, Yue Wu, Ross Pearson +4
COVID-19 appeared abruptly in early 2020, requiring a rapid response amid a context of great uncertainty. Good quality data and knowledge was initially lacking, and many early mode…
The practice of qualitative parameterisation in the development of Bayesian networks
Steven Mascaro, Owen Woodberry, Yue Wu +1
The typical phases of Bayesian network (BN) structured development include specification of purpose and scope, structure development, parameterisation and validation. Structure dev…
BARD: A structured technique for group elicitation of Bayesian networks to support analytic reasoning
Ann E. Nicholson, Kevin B. Korb, Erik P. Nyberg +13
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is…
Latent Variable Discovery Using Dependency Patterns
Xuhui Zhang, Kevin B. Korb, Ann E. Nicholson +1
The causal discovery of Bayesian networks is an active and important research area, and it is based upon searching the space of causal models for those which can best explain a pat…