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 *

204 related articles for article (PubMed ID: 35074389)

  • 1. 24-Hour prediction of PM
    Teng M; Li S; Xing J; Song G; Yang J; Dong J; Zeng X; Qin Y
    Sci Total Environ; 2022 May; 821():153276. PubMed ID: 35074389
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Integration of complete ensemble empirical mode decomposition with deep long short-term memory model for particulate matter concentration prediction.
    Fu M; Le C; Fan T; Prakapovich R; Manko D; Dmytrenko O; Lande D; Shahid S; Yaseen ZM
    Environ Sci Pollut Res Int; 2021 Dec; 28(45):64818-64829. PubMed ID: 34318419
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition.
    Wu X; Zhu J; Wen Q
    PLoS One; 2024; 19(5):e0299603. PubMed ID: 38728371
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A hybrid deep learning technology for PM
    Zhang Z; Zeng Y; Yan K
    Environ Sci Pollut Res Int; 2021 Aug; 28(29):39409-39422. PubMed ID: 33759095
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Daily PM2.5 concentration prediction based on variational modal decomposition and deep learning for multi-site temporal and spatial fusion of meteorological factors.
    Xie X; Wang Z; Xu M; Xu N
    Environ Monit Assess; 2024 Aug; 196(9):859. PubMed ID: 39207594
    [TBL] [Abstract][Full Text] [Related]  

  • 6. PM
    Yang M; Fan H; Zhao K
    Int J Environ Res Public Health; 2019 Nov; 16(22):. PubMed ID: 31739449
    [TBL] [Abstract][Full Text] [Related]  

  • 7. PM2.5 concentration forecasting at surface monitoring sites using GRU neural network based on empirical mode decomposition.
    Huang G; Li X; Zhang B; Ren J
    Sci Total Environ; 2021 May; 768():144516. PubMed ID: 33453525
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A new combination model using decomposition ensemble framework and error correction technique for forecasting hourly PM
    Yang H; Wang C; Li G
    J Environ Manage; 2022 Sep; 318():115498. PubMed ID: 35728375
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An ensemble long short-term memory neural network for hourly PM
    Bai Y; Zeng B; Li C; Zhang J
    Chemosphere; 2019 May; 222():286-294. PubMed ID: 30708163
    [TBL] [Abstract][Full Text] [Related]  

  • 10. PM2.5 forecasting for an urban area based on deep learning and decomposition method.
    Zaini N; Ean LW; Ahmed AN; Abdul Malek M; Chow MF
    Sci Rep; 2022 Oct; 12(1):17565. PubMed ID: 36266317
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A hybrid model for enhanced forecasting of PM
    Feng X; Zhang X; Henne S; Zhao YB; Liu J; Chen TL; Wang J
    Environ Pollut; 2024 Aug; 355():124263. PubMed ID: 38815889
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Long short-term memory - Fully connected (LSTM-FC) neural network for PM
    Zhao J; Deng F; Cai Y; Chen J
    Chemosphere; 2019 Apr; 220():486-492. PubMed ID: 30594800
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Forecasting air pollutant concentration using a novel spatiotemporal deep learning model based on clustering, feature selection and empirical wavelet transform.
    Kim J; Wang X; Kang C; Yu J; Li P
    Sci Total Environ; 2021 Dec; 801():149654. PubMed ID: 34416605
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Particulate Matter Concentration Prediction Model Based on Long Short-Term Memory and an Artificial Neural Network.
    Park J; Chang S
    Int J Environ Res Public Health; 2021 Jun; 18(13):. PubMed ID: 34202834
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.
    Li X; Peng L; Yao X; Cui S; Hu Y; You C; Chi T
    Environ Pollut; 2017 Dec; 231(Pt 1):997-1004. PubMed ID: 28898956
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Sequential prediction of quantitative health risk assessment for the fine particulate matter in an underground facility using deep recurrent neural networks.
    Loy-Benitez J; Vilela P; Li Q; Yoo C
    Ecotoxicol Environ Saf; 2019 Mar; 169():316-324. PubMed ID: 30458398
    [TBL] [Abstract][Full Text] [Related]  

  • 17. DESA: a novel hybrid decomposing-ensemble and spatiotemporal attention model for PM
    Fang S; Li Q; Karimian H; Liu H; Mo Y
    Environ Sci Pollut Res Int; 2022 Aug; 29(36):54150-54166. PubMed ID: 35294690
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A hybrid model for forecasting of particulate matter concentrations based on multiscale characterization and machine learning techniques.
    Ali Shah SA; Aziz W; Almaraashi M; Ahmed Nadeem MS; Habib N; Shim SO
    Math Biosci Eng; 2021 Mar; 18(3):1992-2009. PubMed ID: 33892534
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Short-term prediction of urban PM
    Chu J; Dong Y; Han X; Xie J; Xu X; Xie G
    Environ Sci Pollut Res Int; 2021 Jan; 28(1):56-72. PubMed ID: 33044693
    [TBL] [Abstract][Full Text] [Related]  

  • 20. PM2.5 concentration modeling and prediction by using temperature-based deep belief network.
    Xing H; Wang G; Liu C; Suo M
    Neural Netw; 2021 Jan; 133():157-165. PubMed ID: 33217684
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.