ArticleIranian journal of public health2020
A Hybrid of Structural Equation Modeling and Artificial Neural Networks to Predict Motorcyclists' Injuries: A Conceptual Model in a Case-Control Study.
Article in Iranian journal of public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 6 citations in OpenAlex.
- Article
- A Hybrid of Random Forests and Generalized Path Analysis: A Causal Modeling of Crashes in 52,524 Suburban Areas.Journal of research in health sciences · 2023Article
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3 authors at 1 institution in 1 country.
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Abstract
backgroundTo model, the predictors of injuries caused the hospitalization of motorcyclists using a hybrid structural equation modeling-artificial neural network (SEM-ANN) considering a conceptual model.
methodsIn this case-control study, 300 cases and 156 controls were enrolled using a cluster random sampling. The cases were selected among injured motorcyclists in refereed to Imam Reza Hospital and Tabriz Shohada Hospital, Tabriz, Iran since Mar 2013. The predictability of injury by motorcycle-riding behavior questionnaire (MRBQ), Attention-deficit/hyperactivity disorder (ADHD) along with its subscales and motorcycle related variables was modeled using SEM-ANN. By SEM, linear direct and indirect relationships were assessed. To improve the SEM, the ANN was utilized sequentially to account for the nonlinear and interaction effects that is not supported by SEM.
resultsThe predictors of injury were: MRBQ, ADHD, and its subscales, marital status, education level, riding for fun, engine volume, hyper active child, dark hour riding, cell phone answering, driving license (All
conclusionThe hybrid model provided results that are more accurate; considering the results of the modeling, having intervention programs on ADHD motorcyclists, those have the hyperactive child, and those who answer their cell phones while driving, and improving the motorcyclists' goal is highly recommended.
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