Utilizing machine learning and geographic analysis to improve Post-crash traffic injury management and emergency response systems [0.03%]
利用机器学习和地理分析改善交通事故后损伤管理及应急反应系统
Boonsak Hanterdsith
Boonsak Hanterdsith
Traffic injuries are a major public health concern globally. This study uses machine learning (ML) and geographic analysis to analyse road traffic fatalities and improve traffic safety in Nakhon Ratchasima Province, Thailand. Data on road t...
Examining fatal and non-fatal injuries of drivers in single-vehicle-involved crashes on urban roadways using random parameter logit model [0.03%]
基于随机参数逻辑模型的城市道路单方交通事故中驾驶员伤亡分析方法研究
Charles Atombo,Raymond Akuh,Richard Fiifi Turkson et al.
Charles Atombo et al.
Urban areas significantly impact crash injury severity due to high traffic density and complex road patterns. This study analysed factors influencing fatal and non-fatal injuries in single-vehicle crashes on urban roads in Ghana from 2017 t...
Stacking models for analyzing traffic injury severity on two-lane, two-way rural roads [0.03%]
基于双车道双向公路的交通伤情严重程度分析模型堆叠方法研究
Ali Tavakoli Kashani,Parsa Soleyman Farahani,Hamzeh Mansouri Kargar
Ali Tavakoli Kashani
The analysis of injury severity in accidents allows traffic management agencies to assess crash risk more effectively and develop cost-effective interventions. The aim of this research is to present a two-layer stacking model as a means of ...
An analysis of occupational illness and injuries of the industrial workers in slums [0.03%]
贫民窟工业工人职业病和工伤分析
Shashwati Banerjee,Kishor Goswami
Shashwati Banerjee
The achievement of Sustainable Development Goals 3 (Good Health and Well-Being) and 8 (Decent Work and Economic Growth) requires addressing the occupational health challenges and unsafe working conditions faced by industrial workers in slum...
Effectiveness of IRAP at reducing road traffic injuries: urgent need for research on what works in road design in LMICs [0.03%]
关于在发展中国家进行道路设计研究的紧迫性以减少道路交通伤害：亟待查明何种方法行之有效
Independent Council for Road Safety International
Independent Council for Road Safety International
A recently published impact evaluation overstates the benefits of IRAP protocols in reducing traffic injuries. This ICoRSI Position Statement clarifies the biases in the methods used in this study and how its findings should be interpreted....
Analysis of motorcyclist injury severities in motorcyclist violation crash on suburban roads of China: accommodating temporal instability and the unobserved heterogeneity in means and variances [0.03%]
中国郊区摩托车违章事故中摩托车手受伤程度的分析：包容时间不稳定性和均值及方差未观察异质性
Yuntao Ye,Jie He,Xintong Yan
Yuntao Ye
This study analysed motorcyclist violation (MV) crashes on suburban roads of China to investigate how determinants affect MV crash injury severity and explore the temporal stability of determinants. Crash data from Xi'an, China (2015-2018) ...
Clinical outcomes of patients with crush syndrome in the Kahramanmaras earthquake [0.03%]
卡赫拉曼马拉什地震 Crush 综合征患者的临床结局
Umit Cakmak,Suleyman Akkaya,Ramazan Danis et al.
Umit Cakmak et al.
Earthquakes are among the most devastating natural disasters, often resulting in significant loss of life and widespread injuries. Crush syndrome (CS), a systemic manifestation of muscle injury due to prolonged compression, is a critical co...
Pattern of road traffic fatalities in India: a case study of Chhattisgarh State [0.03%]
印度道路交通死亡事故模式：恰蒂斯加尔邦案例研究
Arunabha Banerjee,Geetam Tiwari,Asha S Viswanathan et al.
Arunabha Banerjee et al.
India does not have a national crash-level surveillance system. Instead, police stations report crashes in standardized tables that are summarized at the state level. Since tabulations provide limited insights into crash patterns, we develo...
Assessing the interdependence of rider fault-status and injury severity in motorcycle rear-end crashes: insights from bivariate probit and XGBoost-SHAP models [0.03%]
摩托车追尾碰撞中骑手故障状态与伤情严重程度相互依赖性的评估：来自二元Probit和XGBoost-SHAP模型的见解
Chamroeun Se,Thanapong Champahom,Kestsirin Theerathitichaipa et al.
Chamroeun Se et al.
This study examines the interdependent relationship between fault status and injury severity in motorcycle rear-end crashes in Thailand using data from 1,549 crashes (2011-2015) integrated from the Department of Highway's Accident Informati...
Bicycle crash frequency modeling across different crash severities using a random-forest-based Shapley Additive explanations approach [0.03%]
基于随机森林的Shapley加性解释方法在不同事故严重程度下自行车事故频率建模
Tao Li,Ruiqi Wang,Hongliang Ding et al.
Tao Li et al.
Statistical modeling and data-driven studies on bicycle accidents are widespread, however, explanations of the underlying mechanisms remain limited, particularly regarding the impact of key risk factors on the bicycle crash frequency across...