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 *

103 related articles for article (PubMed ID: 33385620)

  • 1. Injury risk assessment based on pre-crash variables: The role of closing velocity and impact eccentricity.
    Gulino MS; Gangi LD; Sortino A; Vangi D
    Accid Anal Prev; 2021 Feb; 150():105864. PubMed ID: 33385620
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparison and validation of injury risk classifiers for advanced automated crash notification systems.
    Kusano K; Gabler HC
    Traffic Inj Prev; 2014; 15 Suppl 1():S126-33. PubMed ID: 25307377
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evaluation of Vehicle-Based Crash Severity Metrics.
    Tsoi AH; Gabler HC
    Traffic Inj Prev; 2015; 16 Suppl 2():S132-9. PubMed ID: 26436222
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Association Between NCAP Ratings and Real-World Rear Seat Occupant Risk of Injury.
    Metzger KB; Gruschow S; Durbin DR; Curry AE
    Traffic Inj Prev; 2015; 16 Suppl 2():S146-52. PubMed ID: 26436224
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Characteristics of crashes that increase the risk of serious injuries.
    Augenstein J; Perdeck E; Stratton J; Digges K; Bahouth G
    Annu Proc Assoc Adv Automot Med; 2003; 47():561-76. PubMed ID: 12941251
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Crash Telemetry-Based Injury Severity Prediction is Equivalent to or Out-Performs Field Protocols in Triage of Planar Vehicle Collisions.
    He K; Zhang P; Wang SC
    Prehosp Disaster Med; 2019 Aug; 34(4):356-362. PubMed ID: 31322099
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Evaluation of NASS-CDS side crash delta-V estimates using event data recorders.
    Johnson NS; Gabler HC
    Traffic Inj Prev; 2014; 15(8):827-34. PubMed ID: 24433050
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Analysis of delta velocity and PDOF by means of collision partner and structural involvement in real-life crash pulses with modern passenger cars.
    Iraeus J; Lindquist M
    Traffic Inj Prev; 2014; 15(1):56-65. PubMed ID: 24279967
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of thoracic injury severity in frontal impacts by selected anatomical morphomic variables through model-averaged logistic regression approach.
    Zhang P; Parenteau C; Wang L; Holcombe S; Kohoyda-Inglis C; Sullivan J; Wang S
    Accid Anal Prev; 2013 Nov; 60():172-80. PubMed ID: 24060439
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Numerical investigation of occupant injury risks in car-to-end terminal crashes using dummy-based injury criteria and vehicle-based crash severity metrics.
    Meng Y; Untaroiu C
    Accid Anal Prev; 2020 Sep; 145():105700. PubMed ID: 32777560
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Crash safety concerns for out-of-position occupant postures: A look toward safety in highly automated vehicles.
    McMurry TL; Poplin GS; Shaw G; Panzer MB
    Traffic Inj Prev; 2018; 19(6):582-587. PubMed ID: 29630403
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A data-driven, kinematic feature-based, near real-time algorithm for injury severity prediction of vehicle occupants.
    Wang Q; Gan S; Chen W; Li Q; Nie B
    Accid Anal Prev; 2021 Jun; 156():106149. PubMed ID: 33933716
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Secondary collisions revisited: real-world crash data and relationship to crash test criteria.
    Gowat RC; Gabauer DJ
    Traffic Inj Prev; 2013; 14(1):46-55. PubMed ID: 23259518
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes.
    Kononen DW; Flannagan CA; Wang SC
    Accid Anal Prev; 2011 Jan; 43(1):112-22. PubMed ID: 21094304
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A comparative study on machine learning based algorithms for prediction of motorcycle crash severity.
    Wahab L; Jiang H
    PLoS One; 2019; 14(4):e0214966. PubMed ID: 30947250
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Comparison of pregnant and non-pregnant occupant crash and injury characteristics based on national crash data.
    Manoogian S
    Accid Anal Prev; 2015 Jan; 74():69-76. PubMed ID: 25463946
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comprehensive target populations for current active safety systems using national crash databases.
    Kusano KD; Gabler HC
    Traffic Inj Prev; 2014; 15(7):753-61. PubMed ID: 24433115
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Effectiveness of the revision to FMVSS 301: FARS and NASS-CDS analysis of fatalities and severe injuries in rear impacts.
    Viano DC; Parenteau CS
    Accid Anal Prev; 2016 Apr; 89():1-8. PubMed ID: 26773695
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Rear seat safety: Variation in protection by occupant, crash and vehicle characteristics.
    Durbin DR; Jermakian JS; Kallan MJ; McCartt AT; Arbogast KB; Zonfrillo MR; Myers RK
    Accid Anal Prev; 2015 Jul; 80():185-92. PubMed ID: 25912100
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Does unbelted safety requirement affect protection for belted occupants?
    Hu J; Klinich KD; Manary MA; Flannagan CAC; Narayanaswamy P; Reed MP; Andreen M; Neal M; Lin CH
    Traffic Inj Prev; 2017 May; 18(sup1):S85-S95. PubMed ID: 28296431
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.