We combine knowledge with available Demographic and Health Survey (DHS) data from India, to construct Causal Bayesian Networks (CBNs) and investigate the ...
We make use of freeware tools to learn the graphical structure of the DHS data with score-based, constraint-based, and hybrid structure learning algorithms. We ...
Learning Bayesian networks from demographic and health survey data. View/Open. Accepted version (1.762Mb). Publisher. Elsevier. Publisher URL.
Applications of Bayesian networks in assessing the effects of family resilience on caregiver behavioral problems, depressive symptoms, and burdens · Psychology, ...
People also ask
How do I learn Bayesian network?
How are Bayesian networks useful for medical diagnosis?
What is the difference between machine learning and Bayesian networks?
Why learn Bayesian networks?
The goal of this survey is to provide continuous information about the major social fields of population, housing, education, employment, health and income.
Secondary data analysis using Evidence-Based Bayesian ...
www.sciencedirect.com › article › abs › pii
Aug 7, 2024 · This paper presents a systematic method of building BNs based on secondary data. We build the BN structure based on published evidence and expert interviews.
Jul 4, 2024 · This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most ...
the impact of social, demographic and healthcare variables through a data-driven Bayesian Decision Network. We do this by learning a joint probabilistic ...
Dec 29, 2023 · We aimed to develop and validate a predictive model that exhibits high performance with data sets that contain missing and censored data.
Jun 17, 2020 · In this study, we explored application of Bayesian networks for predicting long-term outcomes after bariatric surgery in a national registry.
Missing: survey | Show results with:survey