BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

279 related articles for article (PubMed ID: 23348101)

  • 21. 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]  

  • 22. Unsafe Bicycling Behavior in Changsha, China: A Video-Based Observational Study.
    Gao Y; Schwebel DC; Zhang L; Xiao W; Hu G
    Int J Environ Res Public Health; 2020 May; 17(9):. PubMed ID: 32392761
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Investigating factors affecting riders' behaviors of occupying motorized vehicle lanes on urban streets.
    Zhang W; Zhou C; Huang W; Tao H; Wang K; Feng Z; Hu Z
    Accid Anal Prev; 2019 Jan; 122():127-133. PubMed ID: 30343164
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Influences of motorcycle rider and driver characteristics and road environment on red light running behavior at signalized intersections.
    Jensupakarn A; Kanitpong K
    Accid Anal Prev; 2018 Apr; 113():317-324. PubMed ID: 29471234
    [TBL] [Abstract][Full Text] [Related]  

  • 25. An analysis of cyclists' speed at combined pedestrian and cycle paths.
    Eriksson J; Forsman Å; Niska A; Gustafsson S; Sörensen G
    Traffic Inj Prev; 2019; 20(sup3):56-61. PubMed ID: 31560212
    [No Abstract]   [Full Text] [Related]  

  • 26. Red-light running behavior of cyclists in Italy: An observational study.
    Fraboni F; Marín Puchades V; De Angelis M; Pietrantoni L; Prati G
    Accid Anal Prev; 2018 Nov; 120():219-232. PubMed ID: 30172107
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Evaluating alternate discrete outcome frameworks for modeling riders' red light running behavior.
    Su X; Yang X; Gao Z; Song D
    Accid Anal Prev; 2023 Oct; 191():107232. PubMed ID: 37506407
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Road factors and bicycle-motor vehicle crashes at unsignalized priority intersections.
    Schepers JP; Kroeze PA; Sweers W; Wüst JC
    Accid Anal Prev; 2011 May; 43(3):853-61. PubMed ID: 21376876
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 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]  

  • 30. 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]  

  • 31. 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]  

  • 32. Mobile phone use among motorcyclists and electric bike riders: A case study of Hanoi, Vietnam.
    Truong LT; Nguyen HT; De Gruyter C
    Accid Anal Prev; 2016 Jun; 91():208-15. PubMed ID: 27015225
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Risk Riding Behaviors of Urban E-Bikes: A Literature Review.
    Ma C; Yang D; Zhou J; Feng Z; Yuan Q
    Int J Environ Res Public Health; 2019 Jun; 16(13):. PubMed ID: 31261838
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Safety effects of permanent running lights for bicycles: A controlled experiment.
    Madsen JC; Andersen T; Lahrmann HS
    Accid Anal Prev; 2013 Jan; 50():820-9. PubMed ID: 22884376
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Speed choice and mental workload of elderly cyclists on e-bikes in simple and complex traffic situations: a field experiment.
    Vlakveld WP; Twisk D; Christoph M; Boele M; Sikkema R; Remy R; Schwab AL
    Accid Anal Prev; 2015 Jan; 74():97-106. PubMed ID: 25463949
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Analysis of road traffic accidents and casualties associated with electric bikes and bicycles in Guangzhou, China: A retrospective descriptive analysis.
    Zhou N; Zeng H; Xie R; Yang T; Kong J; Song Z; Zhang F; Liao X; Chen X; Miao Q; Lan F; Zhao W; Han R; Li D
    Heliyon; 2024 May; 10(9):e29961. PubMed ID: 38694049
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Secondary task engagement, risk-taking, and safety-related equipment use in German bicycle and e-scooter riders - An observation.
    Huemer AK; Banach E; Bolten N; Helweg S; Koch A; Martin T
    Accid Anal Prev; 2022 Jul; 172():106685. PubMed ID: 35490473
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Cyclist activity and injury risk analysis at signalized intersections: a Bayesian modelling approach.
    Strauss J; Miranda-Moreno LF; Morency P
    Accid Anal Prev; 2013 Oct; 59():9-17. PubMed ID: 23743297
    [TBL] [Abstract][Full Text] [Related]  

  • 39. E-bikers' braking behavior: Results from a naturalistic cycling study.
    Huertas-Leyva P; Dozza M; Baldanzini N
    Traffic Inj Prev; 2019; 20(sup3):62-67. PubMed ID: 31442089
    [No Abstract]   [Full Text] [Related]  

  • 40. Red-light running rates at five intersections by road user in Changsha, China: An observational study.
    Yan F; Li B; Zhang W; Hu G
    Accid Anal Prev; 2016 Oct; 95(Pt B):381-386. PubMed ID: 26152610
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 14.