Abstract: A new way to improve vehicle stability analysis is to combine IoT sensors with sophisticated analytical methods like Bayesian networks. It investigates how to use Bayesian networks to handle ...

Bayesian random-effects NMAs estimated odds ratios (ORs) with 95% credible intervals (CrIs), complementary frequentist NMAs provided 95% confidence intervals and 95% prediction intervals. Results: ...

This webinar introduced healthcare researchers to Bayesian meta-analysis methods, challenging the perception that these methods are inaccessible to non-statistical researchers. The session ...

Abstract: In this study, a Bayesian network method was utilized to establish a Bayesian network model, determine the relative importance of key influencing factors of the old residential communities ...

Post-stroke constipation (PSC) is a common complication among stroke patients, with a positive correlation to stroke severity. Straining during defecation in constipated patients can increase ...

Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

The rapid expansion of higher education has introduced new safety challenges in university laboratories, where fire incidents now represent a critical threat to campus safety. In this paper, we ...

ABSTRACT: This study presents an integrated Multi-Criteria Decision-Making (MCDM) framework for sustainable landfill site selection in Chegutu Municipality, Zimbabwe. Combining the Analytical ...

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...