These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

128 related articles for article (PubMed ID: 38901161)

  • 1. Optimizing crash risk models for freeway segments: A focus on the heterogeneous effects of road geometric design features, traffic operation status, and crash units.
    Li J; Li C; Zhao X
    Accid Anal Prev; 2024 Sep; 205():107665. PubMed ID: 38901161
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Estimating mountainous freeway crash rate: Application of a spatial model with three-dimensional (3D) alignment parameters.
    Wang J; He S; Zhai X; Wang Z; Fu X
    Accid Anal Prev; 2022 Jun; 170():106634. PubMed ID: 35344798
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Safety impacts of geometric design on freeway segments with closely spaced entrance and exit ramps.
    Zhao J; Guo Y; Liu P
    Accid Anal Prev; 2021 Dec; 163():106461. PubMed ID: 34700250
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Using hierarchical Bayesian binary probit models to analyze crash injury severity on high speed facilities with real-time traffic data.
    Yu R; Abdel-Aty M
    Accid Anal Prev; 2014 Jan; 62():161-7. PubMed ID: 24172082
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Understanding crash mechanism on urban expressways using high-resolution traffic data.
    Hossain M; Muromachi Y
    Accid Anal Prev; 2013 Aug; 57():17-29. PubMed ID: 23628939
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Investigating factors of crash frequency with random effects and random parameters models: New insights from Chinese freeway study.
    Hou Q; Tarko AP; Meng X
    Accid Anal Prev; 2018 Nov; 120():1-12. PubMed ID: 30075358
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou, China.
    Zhou Z; Meng F; Song C; Sze NN; Guo Z; Ouyang N
    J Safety Res; 2021 Jun; 77():105-113. PubMed ID: 34092300
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Effect of driver's age and side of impact on crash severity along urban freeways: a mixed logit approach.
    Haleem K; Gan A
    J Safety Res; 2013 Sep; 46():67-76. PubMed ID: 23932687
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.
    Yu R; Wang X; Abdel-Aty M
    Accid Anal Prev; 2017 Apr; 101():37-43. PubMed ID: 28187338
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Impact of traffic states on freeway crash involvement rates.
    Yeo H; Jang K; Skabardonis A; Kang S
    Accid Anal Prev; 2013 Jan; 50():713-23. PubMed ID: 22795398
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Crash severity along rural mountainous highways in Malaysia: An application of a combined decision tree and logistic regression model.
    Rusli R; Haque MM; Saifuzzaman M; King M
    Traffic Inj Prev; 2018; 19(7):741-748. PubMed ID: 29932734
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Identifying crash-prone traffic conditions under different weather on freeways.
    Xu C; Wang W; Liu P
    J Safety Res; 2013 Sep; 46():135-44. PubMed ID: 23932695
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A mixed logit model with mean-variance heterogeneity to investigate factors of crash occurrence.
    Huo X; Leng J; Luo L; Wang D
    Int J Inj Contr Saf Promot; 2021 Sep; 28(3):301-308. PubMed ID: 34013845
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Development of a real-time crash risk prediction model incorporating the various crash mechanisms across different traffic states.
    Xu C; Wang W; Liu P; Zhang F
    Traffic Inj Prev; 2015; 16(1):28-35. PubMed ID: 24697528
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Transferability and robustness of real-time freeway crash risk assessment.
    Shew C; Pande A; Nuworsoo C
    J Safety Res; 2013 Sep; 46():83-90. PubMed ID: 23932689
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Safety performance of traffic phases and phase transitions in three phase traffic theory.
    Xu C; Liu P; Wang W; Li Z
    Accid Anal Prev; 2015 Dec; 85():45-57. PubMed ID: 26367463
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Crash risk analysis for Shanghai urban expressways: A Bayesian semi-parametric modeling approach.
    Yu R; Wang X; Yang K; Abdel-Aty M
    Accid Anal Prev; 2016 Oct; 95(Pt B):495-502. PubMed ID: 26847949
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A negative binomial Lindley approach considering spatiotemporal effects for modeling traffic crash frequency with excess zeros.
    Wang W; Yang Y; Yang X; Gayah VV; Wang Y; Tang J; Yuan Z
    Accid Anal Prev; 2024 Nov; 207():107741. PubMed ID: 39137658
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Evaluation of the impacts of traffic states on crash risks on freeways.
    Xu C; Liu P; Wang W; Li Z
    Accid Anal Prev; 2012 Jul; 47():162-71. PubMed ID: 22405245
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Investigating the different characteristics of weekday and weekend crashes.
    Yu R; Abdel-Aty M
    J Safety Res; 2013 Sep; 46():91-7. PubMed ID: 23932690
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.