BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

258 related articles for article (PubMed ID: 32673377)

  • 1. Good times bad times: Automated forecasting of seasonal cryptosporidiosis in Ontario using machine learning.
    Berke O; Trotz-Williams L; de Montigny S
    Can Commun Dis Rep; 2020 Jun; 46(6):192-197. PubMed ID: 32673377
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Forecasting seasonal influenza activity in Canada-Comparing seasonal Auto-Regressive integrated moving average and artificial neural network approaches for public health preparedness.
    Orang A; Berke O; Poljak Z; Greer AL; Rees EE; Ng V
    Zoonoses Public Health; 2024 May; 71(3):304-313. PubMed ID: 38331569
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models.
    Adeyinka DA; Muhajarine N
    BMC Med Res Methodol; 2020 Dec; 20(1):292. PubMed ID: 33267817
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Forecasting of monthly relative humidity in Delhi, India, using SARIMA and ANN models.
    Shad M; Sharma YD; Singh A
    Model Earth Syst Environ; 2022; 8(4):4843-4851. PubMed ID: 35434264
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Applying SARIMA, ETS, and hybrid models for prediction of tuberculosis incidence rate in Taiwan.
    Kuan MM
    PeerJ; 2022; 10():e13117. PubMed ID: 36164599
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Hybrid Approach Based on Seasonal Autoregressive Integrated Moving Average and Neural Network Autoregressive Models to Predict Scorpion Sting Incidence in El Oued Province, Algeria, From 2005 to 2020.
    Zenia S; L'Hadj M; Selmane S
    J Res Health Sci; 2023 Sep; 23(3):e00586. PubMed ID: 38315901
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Recurrent neural network architecture for forecasting banana prices in Gujarat, India.
    Kumari P; Goswami V; N H; Pundir RS
    PLoS One; 2023; 18(6):e0275702. PubMed ID: 37319281
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Seasonal autoregressive integrated moving average (SARIMA) time-series model for milk production forecasting in pasture-based dairy cows in the Andean highlands.
    Perez-Guerra UH; Macedo R; Manrique YP; Condori EA; Gonzáles HI; Fernández E; Luque N; Pérez-Durand MG; García-Herreros M
    PLoS One; 2023; 18(11):e0288849. PubMed ID: 37972120
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Seasonality and Trend Forecasting of Tuberculosis Prevalence Data in Eastern Cape, South Africa, Using a Hybrid Model.
    Azeez A; Obaromi D; Odeyemi A; Ndege J; Muntabayi R
    Int J Environ Res Public Health; 2016 Jul; 13(8):. PubMed ID: 27472353
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Seasonal behavior and forecasting trends of tuberculosis incidence in Holy Kerbala, Iraq.
    Mohammed SH; Ahmed MM; Al-Mousawi AM; Azeez A
    Int J Mycobacteriol; 2018; 7(4):361-367. PubMed ID: 30531036
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Epidemiology and time series analysis of human brucellosis in Tebessa province, Algeria, from 2000 to 2020.
    Akermi SE; L'Hadj M; Selmane S
    J Res Health Sci; 2022 Mar; 22(1):e00544. PubMed ID: 36511254
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A new hybrid model SARIMA-ETS-SVR for seasonal influenza incidence prediction in mainland China.
    Zhao D; Zhang R
    J Infect Dev Ctries; 2023 Nov; 17(11):1581-1590. PubMed ID: 38064398
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Study on the prediction effect of a combined model of SARIMA and LSTM based on SSA for influenza in Shanxi Province, China.
    Zhao Z; Zhai M; Li G; Gao X; Song W; Wang X; Ren H; Cui Y; Qiao Y; Ren J; Chen L; Qiu L
    BMC Infect Dis; 2023 Feb; 23(1):71. PubMed ID: 36747126
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Evaluation of prediction models for the malaria incidence in Marodijeh Region, Somaliland.
    Mohamed J; Mohamed AI; Daud EI
    J Parasit Dis; 2022 Jun; 46(2):395-408. PubMed ID: 35692477
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Comparative Analysis of Different Univariate Forecasting Methods in Modelling and Predicting the Romanian Unemployment Rate for the Period 2021-2022.
    Davidescu AA; Apostu SA; Paul A
    Entropy (Basel); 2021 Mar; 23(3):. PubMed ID: 33803384
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study.
    Cheng HY; Wu YC; Lin MH; Liu YL; Tsai YY; Wu JH; Pan KH; Ke CJ; Chen CM; Liu DP; Lin IF; Chuang JH
    J Med Internet Res; 2020 Aug; 22(8):e15394. PubMed ID: 32755888
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Weather variability and the incidence of cryptosporidiosis: comparison of time series poisson regression and SARIMA models.
    Hu W; Tong S; Mengersen K; Connell D
    Ann Epidemiol; 2007 Sep; 17(9):679-88. PubMed ID: 17604645
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Time series analysis-based seasonal autoregressive fractionally integrated moving average to estimate hepatitis B and C epidemics in China.
    Wang YB; Qing SY; Liang ZY; Ma C; Bai YC; Xu CJ
    World J Gastroenterol; 2023 Nov; 29(42):5716-5727. PubMed ID: 38075851
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.