BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

183 related articles for article (PubMed ID: 37553738)

  • 1. Forecasting daily confirmed COVID-19 cases in Algeria using ARIMA models.
    Abdelaziz M; Ahmed A; Riad A; Abderrezak G; Djida AA
    East Mediterr Health J; 2023 Jul; 29(7):515-519. PubMed ID: 37553738
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Forecasting daily confirmed COVID-19 cases in Malaysia using ARIMA models.
    Singh S; Murali Sundram B; Rajendran K; Boon Law K; Aris T; Ibrahim H; Chandra Dass S; Singh Gill B
    J Infect Dev Ctries; 2020 Sep; 14(9):971-976. PubMed ID: 33031083
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of the COVID-19 Pandemic for the Top 15 Affected Countries: Advanced Autoregressive Integrated Moving Average (ARIMA) Model.
    Singh RK; Rani M; Bhagavathula AS; Sah R; Rodriguez-Morales AJ; Kalita H; Nanda C; Sharma S; Sharma YD; Rabaan AA; Rahmani J; Kumar P
    JMIR Public Health Surveill; 2020 May; 6(2):e19115. PubMed ID: 32391801
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Forecasting COVID-19 in Pakistan.
    Ali M; Khan DM; Aamir M; Khalil U; Khan Z
    PLoS One; 2020; 15(11):e0242762. PubMed ID: 33253248
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. Forecasting COVID-19 confirmed cases, deaths and recoveries: Revisiting established time series modeling through novel applications for the USA and Italy.
    Gecili E; Ziady A; Szczesniak RD
    PLoS One; 2021; 16(1):e0244173. PubMed ID: 33411744
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Empirical Evaluation of Alternative Time-Series Models for COVID-19 Forecasting in Saudi Arabia.
    Al-Turaiki I; Almutlaq F; Alrasheed H; Alballa N
    Int J Environ Res Public Health; 2021 Aug; 18(16):. PubMed ID: 34444409
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting the impact of the third wave of COVID-19 in India using hybrid statistical machine learning models: A time series forecasting and sentiment analysis approach.
    Mohan S; Solanki AK; Taluja HK; Anuradha ; Singh A
    Comput Biol Med; 2022 May; 144():105354. PubMed ID: 35240374
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia.
    Tan CV; Singh S; Lai CH; Zamri ASSM; Dass SC; Aris TB; Ibrahim HM; Gill BS
    Int J Environ Res Public Health; 2022 Jan; 19(3):. PubMed ID: 35162523
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Forecasting COVID-19 pandemic in Alberta, Canada using modified ARIMA models.
    Sun J
    Comput Methods Programs Biomed Update; 2021; 1():100029. PubMed ID: 34604831
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Interruption time series analysis using autoregressive integrated moving average model: evaluating the impact of COVID-19 on the epidemic trend of gonorrhea in China.
    Li Y; Liu X; Li X; Xue C; Zhang B; Wang Y
    BMC Public Health; 2023 Oct; 23(1):2073. PubMed ID: 37872621
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prognosticating the Spread of Covid-19 Pandemic Based on Optimal Arima Estimators.
    Sandhir V; Kumar V; Kumar V
    Endocr Metab Immune Disord Drug Targets; 2021; 21(4):586-591. PubMed ID: 33121426
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy.
    Perone G
    Eur J Health Econ; 2022 Aug; 23(6):917-940. PubMed ID: 34347175
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction and analysis of COVID-19 daily new cases and cumulative cases: times series forecasting and machine learning models.
    Wang Y; Yan Z; Wang D; Yang M; Li Z; Gong X; Wu D; Zhai L; Zhang W; Wang Y
    BMC Infect Dis; 2022 May; 22(1):495. PubMed ID: 35614387
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: a case study in endemic districts of Bhutan.
    Wangdi K; Singhasivanon P; Silawan T; Lawpoolsri S; White NJ; Kaewkungwal J
    Malar J; 2010 Sep; 9():251. PubMed ID: 20813066
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of confirmed cases of and deaths caused by COVID-19 in Chile through time series techniques: A comparative study.
    Barría-Sandoval C; Ferreira G; Benz-Parra K; López-Flores P
    PLoS One; 2021; 16(4):e0245414. PubMed ID: 33914758
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Forecasting road accidental deaths in India: an explicit comparison between ARIMA and exponential smoothing method.
    Swain PK; Tripathy MR; Agrawal K
    Int J Inj Contr Saf Promot; 2023 Dec; 30(4):547-560. PubMed ID: 37348002
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 10.