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.
306 related articles for article (PubMed ID: 39135162)
1. Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model. Li G; Li Y; Han G; Jiang C; Geng M; Guo N; Wu W; Liu S; Xing Z; Han X; Li Q BMC Public Health; 2024 Aug; 24(1):2171. PubMed ID: 39135162 [TBL] [Abstract][Full Text] [Related]
2. 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]
3. The prediction of influenza-like illness using national influenza surveillance data and Baidu query data. Wei S; Lin S; Wenjing Z; Shaoxia S; Yuejie Y; Yujie H; Shu Z; Zhong L; Ti L BMC Public Health; 2024 Feb; 24(1):513. PubMed ID: 38369456 [TBL] [Abstract][Full Text] [Related]
4. Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm. Karbasi M; Ali M; Bateni SM; Jun C; Jamei M; Farooque AA; Yaseen ZM Sci Rep; 2024 Jul; 14(1):15051. PubMed ID: 38951605 [TBL] [Abstract][Full Text] [Related]
5. Air quality index forecast in Beijing based on CNN-LSTM multi-model. Zhang J; Li S Chemosphere; 2022 Dec; 308(Pt 1):136180. PubMed ID: 36058367 [TBL] [Abstract][Full Text] [Related]
6. Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation. Yang L; Li G; Yang J; Zhang T; Du J; Liu T; Zhang X; Han X; Li W; Ma L; Feng L; Yang W J Med Internet Res; 2023 Feb; 25():e44238. PubMed ID: 36780207 [TBL] [Abstract][Full Text] [Related]
7. Analysis and forecasting of syphilis trends in mainland China based on hybrid time series models. Wang ZD; Yang CX; Zhang SK; Wang YB; Xu Z; Feng ZJ Epidemiol Infect; 2024 May; 152():e93. PubMed ID: 38800855 [TBL] [Abstract][Full Text] [Related]
8. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition. Zhang X; Zhang Q; Zhang G; Nie Z; Gui Z; Que H Int J Environ Res Public Health; 2018 May; 15(5):. PubMed ID: 29883381 [TBL] [Abstract][Full Text] [Related]
9. Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation. Khullar S; Singh N Environ Sci Pollut Res Int; 2022 Feb; 29(9):12875-12889. PubMed ID: 33988840 [TBL] [Abstract][Full Text] [Related]
10. 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]
11. Trend analysis and prediction of gonorrhea in mainland China based on a hybrid time series model. Wang Z; Wang Y; Zhang S; Wang S; Xu Z; Feng Z BMC Infect Dis; 2024 Jan; 24(1):113. PubMed ID: 38253998 [TBL] [Abstract][Full Text] [Related]
12. Statistical machine learning models for prediction of China's maritime emergency patients in dynamic: ARIMA model, SARIMA model, and dynamic Bayesian network model. Yang P; Cheng P; Zhang N; Luo D; Xu B; Zhang H Front Public Health; 2024; 12():1401161. PubMed ID: 39022407 [TBL] [Abstract][Full Text] [Related]
13. The comparative analysis of SARIMA, Facebook Prophet, and LSTM for road traffic injury prediction in Northeast China. Feng T; Zheng Z; Xu J; Liu M; Li M; Jia H; Yu X Front Public Health; 2022; 10():946563. PubMed ID: 35937210 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands. Butt FM; Hussain L; Mahmood A; Lone KJ Math Biosci Eng; 2020 Dec; 18(1):400-425. PubMed ID: 33525099 [TBL] [Abstract][Full Text] [Related]
17. A novel hybrid model based on two-stage data processing and machine learning for forecasting chlorophyll-a concentration in reservoirs. Yu W; Wang X; Jiang X; Zhao R; Zhao S Environ Sci Pollut Res Int; 2024 Jan; 31(1):262-279. PubMed ID: 38015396 [TBL] [Abstract][Full Text] [Related]
18. LSTM-based recurrent neural network provides effective short term flu forecasting. Amendolara AB; Sant D; Rotstein HG; Fortune E BMC Public Health; 2023 Sep; 23(1):1788. PubMed ID: 37710241 [TBL] [Abstract][Full Text] [Related]
19. Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study. Sudarshan VK; Brabrand M; Range TM; Wiil UK Comput Biol Med; 2021 Aug; 135():104541. PubMed ID: 34166880 [TBL] [Abstract][Full Text] [Related]
20. Long Short-term Memory-Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation. Athanasiou M; Fragkozidis G; Zarkogianni K; Nikita KS J Med Internet Res; 2023 Feb; 25():e42519. PubMed ID: 36745490 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]