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 *

147 related articles for article (PubMed ID: 35077521)

  • 1. A hybrid neural network for driving behavior risk prediction based on distracted driving behavior data.
    Fu X; Meng H; Wang X; Yang H; Wang J
    PLoS One; 2022; 17(1):e0263030. PubMed ID: 35077521
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Hybrid Deep Learning Model for Recognizing Actions of Distracted Drivers.
    Jiao SJ; Liu LY; Liu Q
    Sensors (Basel); 2021 Nov; 21(21):. PubMed ID: 34770728
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Optimally-Weighted Image-Pose Approach (OWIPA) for Distracted Driver Detection and Classification.
    Koay HV; Chuah JH; Chow CO; Chang YL; Rudrusamy B
    Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300577
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Research on a Cognitive Distraction Recognition Model for Intelligent Driving Systems Based on Real Vehicle Experiments.
    Sun Q; Wang C; Guo Y; Yuan W; Fu R
    Sensors (Basel); 2020 Aug; 20(16):. PubMed ID: 32784788
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Modeling distracted driving behavior considering cognitive processes.
    Zhu Y; Yue L; Zhang Q; Sun J
    Accid Anal Prev; 2024 Jul; 202():107602. PubMed ID: 38701561
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A hybrid neural network for large-scale expressway network OD prediction based on toll data.
    Fu X; Yang H; Liu C; Wang J; Wang Y
    PLoS One; 2019; 14(5):e0217241. PubMed ID: 31120962
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Safety critical event prediction through unified analysis of driver and vehicle volatilities: Application of deep learning methods.
    Arvin R; Khattak AJ; Qi H
    Accid Anal Prev; 2021 Mar; 151():105949. PubMed ID: 33385957
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers.
    Oviedo-Trespalacios O; Haque MM; King M; Washington S
    Accid Anal Prev; 2017 Apr; 101():67-77. PubMed ID: 28189943
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Wearable Driver Distraction Identification On-The-Road via Continuous Decomposition of Galvanic Skin Responses.
    Dehzangi O; Rajendra V; Taherisadr M
    Sensors (Basel); 2018 Feb; 18(2):. PubMed ID: 29414902
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A dynamic method to predict driving risk on sharp curves using multi-source data.
    Ma Y; Wang F; Chen S; Xing G; Xie Z; Wang F
    Accid Anal Prev; 2023 Oct; 191():107228. PubMed ID: 37481893
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Examining drivers' eye glance patterns during distracted driving: Insights from scanning randomness and glance transition matrix.
    Wang Y; Bao S; Du W; Ye Z; Sayer JR
    J Safety Res; 2017 Dec; 63():149-155. PubMed ID: 29203013
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Assessment of the Influence of Technology-Based Distracted Driving on Drivers' Infractions and Their Subsequent Impact on Traffic Accidents Severity.
    García-Herrero S; Febres JD; Boulagouas W; Gutiérrez JM; Mariscal Saldaña MÁ
    Int J Environ Res Public Health; 2021 Jul; 18(13):. PubMed ID: 34281092
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Real-time driving risk prediction using a self-attention-based bidirectional long short-term memory network based on multi-source data.
    Xie Z; Ma Y; Zhang Z; Chen S
    Accid Anal Prev; 2024 Sep; 204():107647. PubMed ID: 38796999
    [TBL] [Abstract][Full Text] [Related]  

  • 14. EFFNet-CA: An Efficient Driver Distraction Detection Based on Multiscale Features Extractions and Channel Attention Mechanism.
    Khan T; Choi G; Lee S
    Sensors (Basel); 2023 Apr; 23(8):. PubMed ID: 37112176
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Use of multilevel modeling to examine variability of distracted driving behavior in naturalistic driving studies.
    Freed SA; Ross LA; Gamaldo AA; Stavrinos D
    Accid Anal Prev; 2021 Mar; 152():105986. PubMed ID: 33517207
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Optimizing Road Safety: Advancements in Lightweight YOLOv8 Models and GhostC2f Design for Real-Time Distracted Driving Detection.
    Du Y; Liu X; Yi Y; Wei K
    Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960543
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predictors of Cell Phone Use in Distracted Driving: Extending the Theory of Planned Behavior.
    Tian Y; Robinson JD
    Health Commun; 2017 Sep; 32(9):1066-1075. PubMed ID: 27484152
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting distracted driving: The role of individual differences in working memory.
    Louie JF; Mouloua M
    Appl Ergon; 2019 Jan; 74():154-161. PubMed ID: 30487094
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness.
    Chui KT; Gupta BB; Liu RW; Zhang X; Vasant P; Thomas JJ
    Sensors (Basel); 2021 Sep; 21(19):. PubMed ID: 34640732
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Teens' distracted driving behavior: Prevalence and predictors.
    Gershon P; Zhu C; Klauer SG; Dingus T; Simons-Morton B
    J Safety Res; 2017 Dec; 63():157-161. PubMed ID: 29203014
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.