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Background: Road traffic injuries (RTIs) are currently the ninth most common cause of mortality and are expected to increase in the future. RTIs rank in the top three reasons why young people die. Because of the high incidence and mortality risk, proper trauma care has been prioritized for RTI patients who present to the emergency department.

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Article Synopsis
  • Left ventricular (LV) free wall rupture is a serious and often deadly outcome of a heart attack, specifically after an acute myocardial infarction.
  • A case is presented involving an elderly woman who experienced this rupture following anesthesia induction for a heart surgery, having suffered a heart attack just days earlier.
  • The case underscores the importance of recognizing symptoms and managing severe low blood pressure during surgery, while also discussing the uncommon ways this rupture can manifest and how to effectively treat it.
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Particularly when they occur at high speeds, vehicle accidents represent a serious threat to human beings and due to this fact vehicle accident is considered as worlds high priority risk. Several research have been done to enhance the crashworthiness of bumper subsystems. With an emphasis on the major crash management system components which are also known as crash box and bumper beam, this study explores ways to improve the crashworthiness of vehicles.

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Article Synopsis
  • A classification prediction model using Gradient Boosting Decision Tree (GBDT) is developed to analyze factors leading to escape behaviors in hit-and-run crashes, based on data from the U.S. Crash Report Sampling System (CRSS).
  • GBDT outperforms other common methods like CART, Random Forest, and Logistic Regression, achieving the best metrics (lowest negative log-likelihood, misclassification rate, and highest AUC) and showcasing better computational efficiency.
  • The GBDT model uncovers previously unmentioned factors, such as crash type and relation to the trafficway, and effectively studies interactions between variables, providing valuable insights for improving hit-and-run incident prevention and safety analysis.
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A cross-sectional safety evaluation approach using generalized extreme value models: A case of right-turn safety treatment.

Accid Anal Prev

December 2024

School of Transportation, Southeast University, Nanjing 211189, China; Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 211189, China.

There has been an increase in the use of the extreme value theory (EVT) approach for conflict-based crash risk estimation and its application such as conducting the evaluation of safety countermeasures. This study proposes a cross-sectional approach for evaluating the effectiveness of a right-turn safety treatment using a conflict-based EVT approach. This approach combines traffic conflicts of different sites at the same period and develops the generalized extreme value (GEV) models.

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