Constructing the graphical structure of expert-based Bayesian networks in the context of software engineering: A systematic mapping study

T Rique, M Perkusich, K Gorgônio, H Almeida… - Information and …, 2024 - Elsevier
Context: In scenarios where data availability issues hinder the applications of statistical
causal modeling in software engineering (SE), Bayesian networks (BNs) have been widely …

Learning Bayesian networks with incomplete data by augmentation

T Adel, C de Campos - Proceedings of the AAAI Conference on Artificial …, 2017 - ojs.aaai.org
We present new algorithms for learning Bayesian networks from data with missing values
using a data augmentation approach. An exact Bayesian network learning algorithm is …

Combination of expert decision and learned based Bayesian Networks for multi-scale mechanical analysis of timber elements

HS Sousa, F Prieto-Castrillo, JC Matos… - Expert Systems with …, 2018 - Elsevier
Abstract The use of Bayesian Networks allows to organize and correlate information
gathered from different sources and its optimization may incorporate restrictions adjusting …

Entropy-Based Metrics for URREF Criteria to Assess Uncertainty in Bayesian Networks for Cyber Threat Detection

V Dragos, J Ziegler, JP de Villiers… - 2019 22th …, 2019 - ieeexplore.ieee.org
Bayesian Networks are widely accepted as efficient tools to represent causal models for
decision making under uncertainty. In some applications, networks are built where the …

Semantically enhanced dynamic bayesian network for detecting sepsis mortality risk in ICU patients with infection

T Wang, T Velez, E Apostolova, T Tschampel… - arXiv preprint arXiv …, 2018 - arxiv.org
Although timely sepsis diagnosis and prompt interventions in Intensive Care Unit (ICU)
patients are associated with reduced mortality, early clinical recognition is frequently …

Finding the needle by modeling the haystack: Pulmonary embolism in an emergency patient with cardiorespiratory manifestations

D Luciani, A Magrini, C Berzuini, A Gavazzi… - Expert Systems with …, 2022 - Elsevier
Background: Diagnoses from non-specific symptoms lead to reason over a huge space of
hypotheses. Bayesian Networks (BN) can systematically address the task by integrating …

A Method for Building the Quantitative and Qualitative Part of Bayesian Networks for Intelligent Tutoring Systems

A Ramírez-Noriega, R Juárez-Ramírez… - The Computer …, 2022 - academic.oup.com
The Bayesian network (BN) is an important technique to represent and infer knowledge in
an Intelligent Tutoring System (ITS); however, ITSs are complex to build. Diverse authors …

A Bayesian network approach to classifying bad debt in hospitals

D Shi, J Zurada, J Guan - 2016 49th Hawaii International …, 2016 - ieeexplore.ieee.org
The rising bad debts for unpaid medical treatments in hospitals pose serious problems in
many countries. Researchers have started to use computational intelligence methods to …

Building Syndrome and Symptom Association Network by Bayesian Network

W Qiu, Y Zhang, Z Li, B Cheng - 2018 IEEE 4th International …, 2018 - ieeexplore.ieee.org
The syndrome differentiation and treatment is the basic principle of traditional Chinese
medicine to understand and treat diseases. Data-oriented scientific quantitative analysis on …

Structural refinement of manually created Bayesian network for prostate cancer diagnosis

NK Bhimagavni, T Adilakshmi - International Journal of …, 2021 - inderscienceonline.com
In general, the structure of a Bayesian network can be learnt from the available data. In
some domains like medicine, Bayesian network can be manually created by domain experts …