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 *

262 related articles for article (PubMed ID: 25119882)

  • 1. A hybrid model for predicting the prevalence of schistosomiasis in humans of Qianjiang City, China.
    Zhou L; Yu L; Wang Y; Lu Z; Tian L; Tan L; Shi Y; Nie S; Liu L
    PLoS One; 2014; 9(8):e104875. PubMed ID: 25119882
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Using a Hybrid Model to Forecast the Prevalence of Schistosomiasis in Humans.
    Zhou L; Xia J; Yu L; Wang Y; Shi Y; Cai S; Nie S
    Int J Environ Res Public Health; 2016 Mar; 13(4):355. PubMed ID: 27023573
    [TBL] [Abstract][Full Text] [Related]  

  • 3. [Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model].
    Ke-Wei W; Yu W; Jin-Ping L; Yu-Yu J
    Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi; 2016 Jul; 28(6):630-634. PubMed ID: 29469251
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Time series model for forecasting the number of new admission inpatients.
    Zhou L; Zhao P; Wu D; Cheng C; Huang H
    BMC Med Inform Decis Mak; 2018 Jun; 18(1):39. PubMed ID: 29907102
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China.
    Wu W; Guo J; An S; Guan P; Ren Y; Xia L; Zhou B
    PLoS One; 2015; 10(8):e0135492. PubMed ID: 26270814
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study.
    Wang YW; Shen ZZ; Jiang Y
    BMJ Open; 2019 Jun; 9(6):e025773. PubMed ID: 31209084
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Temporal trends analysis of tuberculosis morbidity in mainland China from 1997 to 2025 using a new SARIMA-NARNNX hybrid model.
    Wang Y; Xu C; Zhang S; Wang Z; Yang L; Zhu Y; Yuan J
    BMJ Open; 2019 Jul; 9(7):e024409. PubMed ID: 31371283
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Forecasting the Tuberculosis Incidence Using a Novel Ensemble Empirical Mode Decomposition-Based Data-Driven Hybrid Model in Tibet, China.
    Li J; Li Y; Ye M; Yao S; Yu C; Wang L; Wu W; Wang Y
    Infect Drug Resist; 2021; 14():1941-1955. PubMed ID: 34079304
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach.
    Ye GH; Alim M; Guan P; Huang DS; Zhou BS; Wu W
    PLoS One; 2021; 16(3):e0248597. PubMed ID: 33725011
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.
    Wang KW; Deng C; Li JP; Zhang YY; Li XY; Wu MC
    Epidemiol Infect; 2017 Apr; 145(6):1118-1129. PubMed ID: 28115032
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Application of a hybrid model in predicting the incidence of tuberculosis in a Chinese population.
    Li Z; Wang Z; Song H; Liu Q; He B; Shi P; Ji Y; Xu D; Wang J
    Infect Drug Resist; 2019; 12():1011-1020. PubMed ID: 31118707
    [No Abstract]   [Full Text] [Related]  

  • 12. Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China.
    Yu L; Zhou L; Tan L; Jiang H; Wang Y; Wei S; Nie S
    PLoS One; 2014; 9(6):e98241. PubMed ID: 24893000
    [TBL] [Abstract][Full Text] [Related]  

  • 13. The research of ARIMA, GM(1,1), and LSTM models for prediction of TB cases in China.
    Zhao D; Zhang H; Cao Q; Wang Z; He S; Zhou M; Zhang R
    PLoS One; 2022; 17(2):e0262734. PubMed ID: 35196309
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks.
    Wu W; An SY; Guan P; Huang DS; Zhou BS
    BMC Infect Dis; 2019 May; 19(1):414. PubMed ID: 31088391
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Forecasting blood demand for different blood groups in Shiraz using auto regressive integrated moving average (ARIMA) and artificial neural network (ANN) and a hybrid approaches.
    Sarvestani SE; Hatam N; Seif M; Kasraian L; Lari FS; Bayati M
    Sci Rep; 2022 Dec; 12(1):22031. PubMed ID: 36539511
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China.
    Wei W; Jiang J; Liang H; Gao L; Liang B; Huang J; Zang N; Liao Y; Yu J; Lai J; Qin F; Su J; Ye L; Chen H
    PLoS One; 2016; 11(6):e0156768. PubMed ID: 27258555
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Seasonality and Trend Forecasting of Tuberculosis Incidence in Chongqing, China.
    Liao Z; Zhang X; Zhang Y; Peng D
    Interdiscip Sci; 2019 Mar; 11(1):77-85. PubMed ID: 30734907
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model.
    Lv CX; An SY; Qiao BJ; Wu W
    BMC Infect Dis; 2021 Aug; 21(1):839. PubMed ID: 34412581
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A New Hybrid Model Using an Autoregressive Integrated Moving Average and a Generalized Regression Neural Network for the Incidence of Tuberculosis in Heng County, China.
    Wei W; Jiang J; Gao L; Liang B; Huang J; Zang N; Ning C; Liao Y; Lai J; Yu J; Qin F; Chen H; Su J; Ye L; Liang H
    Am J Trop Med Hyg; 2017 Sep; 97(3):799-805. PubMed ID: 28820678
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model.
    Liu Q; Liu X; Jiang B; Yang W
    BMC Infect Dis; 2011 Aug; 11():218. PubMed ID: 21838933
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.