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Bicycle-related Crashes in Hong Kong: Is It Possible to Reduce Mortality and Severe Injury in the Metropolitan Area?

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TLDR
Middle-aged casualties, the presence of head injuries, and the involvement of motor vehicles all increase the risk of more severe injury in bicycle-related crashes.
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Bicycle injuries and helmet use: a systematic review and meta-analysis.

TL;DR: Bicycle helmet use was associated with reduced odds of head injury, seriousHead injury, facial injury and fatal head Injury, and the reduction was greater for serious or fatal head injury.
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Bicycle helmets - To wear or not to wear? A meta-analyses of the effects of bicycle helmets on injuries

TL;DR: The results suggest that wearing a helmet while cycling is highly recommendable, especially in situations with an increased risk of single bicycle crashes, such as on slippery or icy roads.
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Using data mining techniques to predict the severity of bicycle crashes.

TL;DR: To investigate the factors predicting severity of bicycle crashes in Italy, an observational study of official statistics was used and two of the most widely used data mining techniques, CHAID decision tree technique and Bayesian network analysis were applied.
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Factors contributing to bicycle–motorised vehicle collisions: a systematic literature review

TL;DR: A comprehensive literature review on Scopus, TRID, ProQuest, and Web of Science databases found evidence that environmental factors may also play a role, although to a lesser extent, in determining BMV collisions.
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Roles of infrastructure and land use in bicycle crash exposure and frequency: A case study using Greater London bike sharing data.

TL;DR: Random parameter negative binomial models are developed to measure the relationship between possible risk factors and bicycle crash frequency at the zonal level, based on the crash data in the Greater London in 2012-2013, and indicate that model taking the bicycle use time as the exposure measure is superior to the other counterparts with the lowest AIC and BIC.
References
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The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care

TL;DR: Results of this investigation indicate that the Injury Severity Score represents an important step in solving the problem of summarizing injury severity, especially in patients with multiple trauma.
Book

Statistical and econometric methods for transportation data analysis

TL;DR: In this paper, the authors proposed a sampling-based approach for estimating Elasticities in time series regression models, which can be used to estimate a single Beta Parameter for m - 1 of the m Levels of a Variable Checking Regression Assumptions Regression Outliers Regression Model GOF Measures Multicollinearity in the Regression Regression model-Building Strategies Estimating Elasticities Censored Dependent Variables-Tobit Model Box-Cox Regression Violations of Regression this paper
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The Injury Severity Score revisited

TL;DR: The present study uses the most recent AIS version (AIS-85) to derive relationships between mortality rate and the iss for comtemporary patients with blunt or penetrating injuries and identifies important properties of the iss which should be considered when the measure is used to compare case mix severity in different populations.
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Influences of Built Environments on Walking and Cycling: Lessons from Bogotá

TL;DR: In this article, the authors examined how road facility designs, like street density, connectivity, and proximity to Ciclovia lanes, are associated with physical activity, while other attributes of the built environment, like density and land-use mixtures, are not.
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Bicyclist injury severities in bicycle–motor vehicle accidents

TL;DR: The results imply that bicyclist fault is more closely correlated with greater bicyclist injury severity than driver fault, which supports the commonly used 30km/h speed limit in residential neighborhoods.
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