Constructing the graphical structure of expert-based Bayesian networks in the context of software engineering: A systematic mapping study
Context: In scenarios where data availability issues hinder the applications of statistical
causal modeling in software engineering (SE), Bayesian networks (BNs) have been widely …
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 …
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
Abstract The use of Bayesian Networks allows to organize and correlate information
gathered from different sources and its optimization may incorporate restrictions adjusting …
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 …
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 …
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 …
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 …
an Intelligent Tutoring System (ITS); however, ITSs are complex to build. Diverse authors …
A Bayesian network approach to classifying bad debt in hospitals
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 …
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 …
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 …
some domains like medicine, Bayesian network can be manually created by domain experts …