BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

359 related articles for article (PubMed ID: 29306685)

  • 1. Road traffic accidents prediction modelling: An analysis of Anambra State, Nigeria.
    Ihueze CC; Onwurah UO
    Accid Anal Prev; 2018 Mar; 112():21-29. PubMed ID: 29306685
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Trends in road traffic accidents in Anambra State, South Eastern Nigeria: need for targeted sensitization on safe roads.
    Anebonam U; Okoli C; Ossai P; Ilesanmi O; Nguku P; Nsubuga P; Abubakar A; Oyemakinde A
    Pan Afr Med J; 2019; 32(Suppl 1):12. PubMed ID: 30949286
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Road safety from the perspective of driver gender and age as related to the injury crash frequency and road scenario.
    Russo F; Biancardo SA; Dell'Acqua G
    Traffic Inj Prev; 2014; 15(1):25-33. PubMed ID: 24279963
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia.
    Tulu GS; Washington S; Haque MM; King MJ
    Accid Anal Prev; 2015 May; 78():118-126. PubMed ID: 25770907
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.
    Zhang X; Pang Y; Cui M; Stallones L; Xiang H
    Ann Epidemiol; 2015 Feb; 25(2):101-6. PubMed ID: 25467006
    [TBL] [Abstract][Full Text] [Related]  

  • 6. On the nature of over-dispersion in motor vehicle crash prediction models.
    Mitra S; Washington S
    Accid Anal Prev; 2007 May; 39(3):459-68. PubMed ID: 17161374
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation.
    Chen C; Zhang G; Liu XC; Ci Y; Huang H; Ma J; Chen Y; Guan H
    Accid Anal Prev; 2016 Dec; 97():69-78. PubMed ID: 27591415
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Bayesian hierarchical statistics for traffic safety modelling and forecasting.
    AlKheder S; Al-Rashidi M
    Int J Inj Contr Saf Promot; 2020 Jun; 27(2):99-111. PubMed ID: 31530077
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Macro-level vulnerable road users crash analysis: A Bayesian joint modeling approach of frequency and proportion.
    Cai Q; Abdel-Aty M; Lee J
    Accid Anal Prev; 2017 Oct; 107():11-19. PubMed ID: 28753415
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads.
    Hosseinpour M; Yahaya AS; Sadullah AF
    Accid Anal Prev; 2014 Jan; 62():209-22. PubMed ID: 24172088
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Applying a random parameters Negative Binomial Lindley model to examine multi-vehicle crashes along rural mountainous highways in Malaysia.
    Rusli R; Haque MM; Afghari AP; King M
    Accid Anal Prev; 2018 Oct; 119():80-90. PubMed ID: 30007211
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Network screening for large urban road networks: Using GPS data and surrogate measures to model crash frequency and severity.
    Stipancic J; Miranda-Moreno L; Saunier N; Labbe A
    Accid Anal Prev; 2019 Apr; 125():290-301. PubMed ID: 30818096
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Validation of the influencing factors associated with traffic violations and crashes on freeways of developing countries: A case study of Iran.
    Hadji Hosseinlou M; Mahdavi A; Jabbari Nooghabi M
    Accid Anal Prev; 2018 Dec; 121():358-366. PubMed ID: 30100049
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Road traffic crashes among farm vehicle drivers in southern China: A cross-sectional survey.
    Zhang X; Yang Y; Chen Y; Yao H; Wu M; Cui M; Li Y; Hu J; Zhang C; Li Z; Stallones L; Xiang H
    Traffic Inj Prev; 2017 Jan; 18(1):83-87. PubMed ID: 27257936
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A crash-prediction model for multilane roads.
    Caliendo C; Guida M; Parisi A
    Accid Anal Prev; 2007 Jul; 39(4):657-70. PubMed ID: 17113552
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Investigation of road network features and safety performance.
    Wang X; Wu X; Abdel-Aty M; Tremont PJ
    Accid Anal Prev; 2013 Jul; 56():22-31. PubMed ID: 23584537
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Impact of data aggregation approaches on the relationships between operating speed and traffic safety.
    Yu R; Quddus M; Wang X; Yang K
    Accid Anal Prev; 2018 Nov; 120():304-310. PubMed ID: 30195137
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A crash-prediction model for road tunnels.
    Caliendo C; De Guglielmo ML; Guida M
    Accid Anal Prev; 2013 Jun; 55():107-15. PubMed ID: 23523897
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Integrated traffic conflict model for estimating crash modification factors.
    Shahdah U; Saccomanno F; Persaud B
    Accid Anal Prev; 2014 Oct; 71():228-35. PubMed ID: 24950130
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.