BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

160 related articles for article (PubMed ID: 35627442)

  • 41. A hazard-based duration model for analyzing crossing behavior of cyclists and electric bike riders at signalized intersections.
    Yang X; Huan M; Abdel-Aty M; Peng Y; Gao Z
    Accid Anal Prev; 2015 Jan; 74():33-41. PubMed ID: 25463942
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Japanese high school students' usage of mobile phones while cycling.
    Ichikawa M; Nakahara S
    Traffic Inj Prev; 2008 Mar; 9(1):42-7. PubMed ID: 18338294
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Comparing the risky behaviours of shared and private e-scooter and bicycle riders in downtown Brisbane, Australia.
    Haworth N; Schramm A; Twisk D
    Accid Anal Prev; 2021 Mar; 152():105981. PubMed ID: 33549973
    [TBL] [Abstract][Full Text] [Related]  

  • 44. 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]  

  • 45. An Analysis of Technology-Related Distracted Biking Behaviors and Helmet Use Among Cyclists in New York City.
    Ethan D; Basch CH; Johnson GD; Hammond R; Chow CM; Varsos V
    J Community Health; 2016 Feb; 41(1):138-45. PubMed ID: 26323983
    [TBL] [Abstract][Full Text] [Related]  

  • 46. More screen operation than calling: the results of observing cyclists' behaviour while using mobile phones.
    de Waard D; Westerhuis F; Lewis-Evans B
    Accid Anal Prev; 2015 Mar; 76():42-8. PubMed ID: 25590920
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Factors affecting the intention to wear helmets for e-bike riders: the case of Chinese college students.
    Yang Y; Li C; Cheng K; Hu S
    Int J Inj Contr Saf Promot; 2024 May; ():1-12. PubMed ID: 38712966
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Mobile phone use among Indonesian motorcyclists: prevalence and influencing factors.
    Widyanti A; Pratama GB; Anindya AH; Sari FP; Sumali A; Salma SA; Yamin PAR; Soetisna HR
    Traffic Inj Prev; 2020; 21(7):459-463. PubMed ID: 32658550
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Psychological predictors of mobile phone use while crossing the street among college students: An application of the theory of planned behavior.
    Jiang K; Ling F; Feng Z; Wang K; Guo L
    Traffic Inj Prev; 2017 Feb; 18(2):118-123. PubMed ID: 27648513
    [TBL] [Abstract][Full Text] [Related]  

  • 50. The prevalence of mobile phone use among motorcyclists in three Mexican cities.
    Pérez-Núñez R; Hidalgo-Solórzano E; Vera-López JD; Lunnen JC; Chandran A; Híjar M; Hyder AA
    Traffic Inj Prev; 2014; 15(2):148-50. PubMed ID: 24345016
    [TBL] [Abstract][Full Text] [Related]  

  • 51. 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]  

  • 52. Explaining Sex Differences in Motorcyclist Riding Behavior: An Application of Multi-Group Structural Equation Modeling.
    Uttra S; Laddawan N; Ratanavaraha V; Jomnonkwao S
    Int J Environ Res Public Health; 2020 Nov; 17(23):. PubMed ID: 33256183
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Examining risky riding behavior in India using Motorcycle rider behavior questionnaire.
    Chouhan SS; Kathuria A; Sekhar CR
    Accid Anal Prev; 2021 Sep; 160():106312. PubMed ID: 34339913
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Using CyclePhilly data to assess wrong-way riding of cyclists in Philadelphia.
    Dhakal N; Cherry CR; Ling Z; Azad M
    J Safety Res; 2018 Dec; 67():145-153. PubMed ID: 30553417
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Risky riding behavior on two wheels: the role of cognitive, social, and personality variables among young adolescents.
    Falco A; Piccirelli A; Girardi D; Dal Corso L; De Carlo NA
    J Safety Res; 2013 Sep; 46():47-57. PubMed ID: 23932685
    [TBL] [Abstract][Full Text] [Related]  

  • 56. The social context of motorcycle riding and the key determinants influencing rider behavior: a qualitative investigation.
    Tunnicliff D; Watson B; White KM; Lewis I; Wishart D
    Traffic Inj Prev; 2011 Aug; 12(4):363-76. PubMed ID: 21823945
    [TBL] [Abstract][Full Text] [Related]  

  • 57. The effects of prompting and reinforcement on safe behavior of bicycle and motorcycle riders.
    Okinaka T; Shimazaki T
    J Appl Behav Anal; 2011; 44(3):671-4. PubMed ID: 21941403
    [TBL] [Abstract][Full Text] [Related]  

  • 58. 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]  

  • 59. 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]  

  • 60. Comparison of Injury Patterns between Electric Bicycle, Bicycle and Motorcycle Accidents.
    Spörri E; Halvachizadeh S; Gamble JG; Berk T; Allemann F; Pape HC; Rauer T
    J Clin Med; 2021 Jul; 10(15):. PubMed ID: 34362145
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.