BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

194 related articles for article (PubMed ID: 33916026)

  • 1. Time Series Forecasting of Univariate Agrometeorological Data: A Comparative Performance Evaluation via One-Step and Multi-Step Ahead Forecasting Strategies.
    Suradhaniwar S; Kar S; Durbha SS; Jagarlapudi A
    Sensors (Basel); 2021 Apr; 21(7):. PubMed ID: 33916026
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Application of one-, three-, and seven-day forecasts during early onset on the COVID-19 epidemic dataset using moving average, autoregressive, autoregressive moving average, autoregressive integrated moving average, and naïve forecasting methods.
    Lynch CJ; Gore R
    Data Brief; 2021 Apr; 35():106759. PubMed ID: 33521186
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Analyzing and Forecasting Pediatric Fever Clinic Visits in High Frequency Using Ensemble Time-Series Methods After the COVID-19 Pandemic in Hangzhou, China: Retrospective Study.
    Zhang W; Zhu Z; Zhao Y; Li Z; Chen L; Huang J; Li J; Yu G
    JMIR Med Inform; 2023 Sep; 11():e45846. PubMed ID: 37728972
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An Intelligent IoT-Cloud-Based Air Pollution Forecasting Model Using Univariate Time-Series Analysis.
    Ansari M; Alam M
    Arab J Sci Eng; 2023 May; ():1-28. PubMed ID: 37361469
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Forecasting the dynamics of cumulative COVID-19 cases (confirmed, recovered and deaths) for top-16 countries using statistical machine learning models: Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA).
    ArunKumar KE; Kalaga DV; Sai Kumar CM; Chilkoor G; Kawaji M; Brenza TM
    Appl Soft Comput; 2021 May; 103():107161. PubMed ID: 33584158
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities.
    Sankalp S; Sahoo BB; Sahoo SN
    Environ Monit Assess; 2023 Jan; 195(2):291. PubMed ID: 36633692
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study.
    Lynch CJ; Gore R
    J Med Internet Res; 2021 Mar; 23(3):e24925. PubMed ID: 33621186
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Using forecast modelling to evaluate treatment effects in single-group interrupted time series analysis.
    Linden A
    J Eval Clin Pract; 2018 Aug; 24(4):695-700. PubMed ID: 29749091
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Model Selection Approach for Time Series Forecasting: Incorporating Google Trends Data in Australian Macro Indicators.
    Karim AA; Pardede E; Mann S
    Entropy (Basel); 2023 Jul; 25(8):. PubMed ID: 37628174
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study.
    Yu CS; Chang SS; Chang TH; Wu JL; Lin YJ; Chien HF; Chen RJ
    J Med Internet Res; 2021 May; 23(5):e27806. PubMed ID: 33900932
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multi-output support vector machine for regional multi-step-ahead PM
    Zhou Y; Chang FJ; Chang LC; Kao IF; Wang YS; Kang CC
    Sci Total Environ; 2019 Feb; 651(Pt 1):230-240. PubMed ID: 30243160
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.
    Ouyang Y; Yin H
    Int J Neural Syst; 2018 May; 28(4):1750053. PubMed ID: 29297261
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Developing a hybrid time-series artificial intelligence model to forecast energy use in buildings.
    Ngo NT; Pham AD; Truong TTH; Truong NS; Huynh NT
    Sci Rep; 2022 Sep; 12(1):15775. PubMed ID: 36131108
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Long-term time-series pollution forecast using statistical and deep learning methods.
    Nath P; Saha P; Middya AI; Roy S
    Neural Comput Appl; 2021; 33(19):12551-12570. PubMed ID: 33840911
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Reinforced two-step-ahead weight adjustment technique for online training of recurrent neural networks.
    Chang LC; Chen PA; Chang FJ
    IEEE Trans Neural Netw Learn Syst; 2012 Aug; 23(8):1269-78. PubMed ID: 24807523
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A stacked machine learning model for multi-step ahead prediction of lake surface water temperature.
    Di Nunno F; Zhu S; Ptak M; Sojka M; Granata F
    Sci Total Environ; 2023 Sep; 890():164323. PubMed ID: 37216992
    [TBL] [Abstract][Full Text] [Related]  

  • 19. PM
    García Nieto PJ; Sánchez Lasheras F; García-Gonzalo E; de Cos Juez FJ
    Sci Total Environ; 2018 Apr; 621():753-761. PubMed ID: 29202286
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A New Auto-Regressive Multi-Variable Modified Auto-Encoder for Multivariate Time-Series Prediction: A Case Study with Application to COVID-19 Pandemics.
    de Oliveira EV; Aragão DP; Gonçalves LMG
    Int J Environ Res Public Health; 2024 Apr; 21(4):. PubMed ID: 38673408
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.