BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

193 related articles for article (PubMed ID: 33653549)

  • 1. Risk factors affecting crash injury severity for different groups of e-bike riders: A classification tree-based logistic regression model.
    Wang Z; Huang S; Wang J; Sulaj D; Hao W; Kuang A
    J Safety Res; 2021 Feb; 76():176-183. PubMed ID: 33653549
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Modeling faults among e-bike-related fatal crashes in China.
    Wang C; Xu C; Xia J; Qian Z
    Traffic Inj Prev; 2017 Feb; 18(2):175-181. PubMed ID: 27763774
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Riding behavior and electric bike traffic crashes: A Chinese case-control study.
    Qian Y; Sun Q; Fei G; Li X; Stallones L; Xiang H; Zhang X
    Traffic Inj Prev; 2020; 21(1):24-28. PubMed ID: 31846600
    [No Abstract]   [Full Text] [Related]  

  • 4. Influence of familiarity with traffic regulations on delivery riders' e-bike crashes and helmet use: Two mediator ordered logit models.
    Wang X; Chen J; Quddus M; Zhou W; Shen M
    Accid Anal Prev; 2021 Sep; 159():106277. PubMed ID: 34246876
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Road traffic injuries among riders of electric bike/electric moped in southern China.
    Zhang X; Yang Y; Yang J; Hu J; Li Y; Wu M; Stallones L; Xiang H
    Traffic Inj Prev; 2018 May; 19(4):417-422. PubMed ID: 29333874
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Underreporting, crash severity and fault assignment of minor crashes in China - a study based on self-reported surveys.
    Yang H; Cherry CR; Su F; Ling Z; Pannell Z; Li Y; Fu Z
    Int J Inj Contr Saf Promot; 2019 Mar; 26(1):30-36. PubMed ID: 29798710
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Casualty risk of e-bike rider struck by passenger vehicle using China in-depth accident data.
    Hu L; Hu X; Wang J; Kuang A; Hao W; Lin M
    Traffic Inj Prev; 2020; 21(4):283-287. PubMed ID: 32297809
    [No Abstract]   [Full Text] [Related]  

  • 8. The effects of sunshields on red light running behavior of cyclists and electric bike riders.
    Zhang Y; Wu C
    Accid Anal Prev; 2013 Mar; 52():210-8. PubMed ID: 23348101
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Factors affecting the injury severity of out-of-control single-vehicle crashes in Singapore.
    Zhou M; Chin HC
    Accid Anal Prev; 2019 Mar; 124():104-112. PubMed ID: 30639682
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Related risk factors for injury severity of e-bike and bicycle crashes in Hefei.
    Hu F; Lv D; Zhu J; Fang J
    Traffic Inj Prev; 2014; 15(3):319-23. PubMed ID: 24372505
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Analysis of factors influencing delivery e-bikes' red-light running behavior: A correlated mixed binary logit approach.
    Zhang F; Ji Y; Lv H; Ma X
    Accid Anal Prev; 2021 Mar; 152():105977. PubMed ID: 33561607
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Characteristics of single-vehicle crashes with e-bikes in Switzerland.
    Hertach P; Uhr A; Niemann S; Cavegn M
    Accid Anal Prev; 2018 Aug; 117():232-238. PubMed ID: 29723734
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A novel approach to investigate effects of front-end structures on injury response of e-bike riders: Combining Monte Carlo sampling, automatic operation, and data mining.
    Liu Y; Wan X; Xu W; Shi L; Bai Z; Wang F
    Accid Anal Prev; 2022 Apr; 168():106599. PubMed ID: 35219105
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The injury epidemiology of adult riders in vehicle-two-wheeler crashes in China, Ningbo, 2011-2015.
    Hu L; Hu X; Wan J; Lin M; Huang J
    J Safety Res; 2020 Feb; 72():21-28. PubMed ID: 32199565
    [TBL] [Abstract][Full Text] [Related]  

  • 15. E-scooter and E-bike injury pattern profile in an inner-city trauma center in upper Manhattan.
    Osti N; Aboud A; Gumbs S; Engdahl R; Carryl S; Donaldson B; Davis R
    Injury; 2023 May; 54(5):1392-1395. PubMed ID: 36882363
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Analyzing E-Bikers' Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model.
    Wang T; Xie S; Ye X; Yan X; Chen J; Li W
    Int J Environ Res Public Health; 2020 Jul; 17(13):. PubMed ID: 32630709
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Risky riding: Naturalistic methods comparing safety behavior from conventional bicycle riders and electric bike riders.
    Langford BC; Chen J; Cherry CR
    Accid Anal Prev; 2015 Sep; 82():220-6. PubMed ID: 26093098
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparative analysis of risky behaviors of electric bicycles at signalized intersections.
    Bai L; Liu P; Guo Y; Yu H
    Traffic Inj Prev; 2015; 16(4):424-8. PubMed ID: 25133656
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Injury Severity of Motorcycle Riders Involved in Traffic Crashes in Hunan, China: A Mixed Ordered Logit Approach.
    Chang F; Li M; Xu P; Zhou H; Haque MM; Huang H
    Int J Environ Res Public Health; 2016 Jul; 13(7):. PubMed ID: 27428987
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Modeling lane-transgressing behavior of e-bike riders on road sections with marked bike lanes: A survival analysis approach.
    Nan S; Yan L; Tu R; Li T
    Traffic Inj Prev; 2021; 22(2):153-157. PubMed ID: 33337927
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 10.