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Data mining approach to model bus crash severity in Australia.
J Safety Res. 2021 Feb;76:73-82. doi: 10.1016/j.jsr.2020.12.004. Epub 2020 Dec 20.
J Safety Res. 2021.
PMID: 33653571
Modelling bus-pedestrian crash severity in the state of Victoria, Australia.
Samerei SA, Aghabayk K, Shiwakoti N, Karimi S.
Samerei SA, et al.
Int J Inj Contr Saf Promot. 2021 Jun;28(2):233-242. doi: 10.1080/17457300.2021.1907597. Epub 2021 Apr 6.
Int J Inj Contr Saf Promot. 2021.
PMID: 33820482
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Using latent class clustering and binary logistic regression to model Australian cyclist injury severity in motor vehicle-bicycle crashes.
Samerei SA, Aghabayk K, Shiwakoti N, Mohammadi A.
Samerei SA, et al.
J Safety Res. 2021 Dec;79:246-256. doi: 10.1016/j.jsr.2021.09.005. Epub 2021 Sep 23.
J Safety Res. 2021.
PMID: 34848005
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Interpretable machine learning for evaluating risk factors of freeway crash severity.
Samerei SA, Aghabayk K.
Samerei SA, et al.
Int J Inj Contr Saf Promot. 2024 May 20:1-17. doi: 10.1080/17457300.2024.2351972. Online ahead of print.
Int J Inj Contr Saf Promot. 2024.
PMID: 38768184
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Analyzing the transition from two-vehicle collisions to chain reaction crashes: A hybrid approach using random parameters logit model, interpretable machine learning, and clustering.
Samerei SA, Aghabayk K.
Samerei SA, et al.
Accid Anal Prev. 2024 Jul;202:107603. doi: 10.1016/j.aap.2024.107603. Epub 2024 May 2.
Accid Anal Prev. 2024.
PMID: 38701559
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