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Evaluation of a Bayesian inference network for ligand-based virtual screening [PDF]
Journal of Cheminformatics, 2009 Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query.
Chen Beining +2 more
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Bayesian networks and decision trees in the diagnosis of female urinary incontinence [PDF]
, 2000 This study compares the effectiveness of Bayesian networks versus Decision Trees in modeling the Integral Theory of Female Urinary Incontinence diagnostic algorithm. Bayesian networks and Decision Trees were developed and trained using data from 58 adult
Hunt, Miranda +3 more
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Bayesian network for predicting mandibular third molar extraction difficulty. [PDF]
BMC Oral HealthBackground This study aimed to establish a model for predicting the difficulty of mandibular third molar extraction based on a Bayesian network to meet following requirements: (1) analyse the interaction of the primary risk factors; (2) output ...
Meng T, Zhang Z, Zhang X, Zhang C.
europepmc +2 more sources
A survey of Bayesian Network structure learning [PDF]
Artificial Intelligence Review, 2021 Bayesian Networks (BNs) have become increasingly popular over the last few decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology, epidemiology, economics and the social sciences. This is especially true in real-world
N. K. Kitson +4 more
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IEEE Access, 2022 To address the problem of low efficiency of the existing hill-climbing algorithm in Bayesian network structure learning, this paper proposes a Bayesian network structure learning algorithm based on probabilistic incremental analysis and constraints.
Haoran Liu +7 more
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Using consensus bayesian network to model the reactive oxygen species regulatory pathway. [PDF]
PLoS ONE, 2013 Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data ...
Liangdong Hu, Limin Wang
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Survey of Research on Non-homogeneous Gene Regulatory Network Models [PDF]
Jisuanji kexue yu tansuo, 2023 In the field of bioinformatics, the construction of gene regulatory networks is crucial. In recent years, non-homogeneous dynamic Bayesian networks have become a common modeling tool for learning gene regulatory networks from gene expression time-series ...
ZHANG Qianqian, HU Chunling, ZHANG Jiayao, LI Dawei, SHAO Mingyi
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Frontiers in Energy Research, 2022 Knowledge-driven and data-driven methods are the two representative categories of intelligent technologies used in fault diagnosis in nuclear power plants.
Ben Qi +3 more
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Students' learning style detection using tree augmented naive Bayes [PDF]
Royal Society Open Science, 2018 Students are characterized according to their own distinct learning styles. Discovering students' learning style is significant in the educational system in order to provide adaptivity.
Ling Xiao Li, Siti Soraya Abdul Rahman
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A Symbolic Approach to Explaining Bayesian Network Classifiers [PDF]
International Joint Conference on Artificial Intelligence, 2018 We propose an approach for explaining Bayesian network classifiers, which is based on compiling such classifiers into decision functions that have a tractable and symbolic form.
Andy Shih, Arthur Choi, Adnan Darwiche
semanticscholar +1 more source