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.
473 related articles for article (PubMed ID: 34200378)
21. Application of a long short-term memory neural network: a burgeoning method of deep learning in forecasting HIV incidence in Guangxi, China. Wang G; Wei W; Jiang J; Ning C; Chen H; Huang J; Liang B; Zang N; Liao Y; Chen R; Lai J; Zhou O; Han J; Liang H; Ye L Epidemiol Infect; 2019 Jan; 147():e194. PubMed ID: 31364559 [TBL] [Abstract][Full Text] [Related]
22. Early Warning and Prediction of Scarlet Fever in China Using the Baidu Search Index and Autoregressive Integrated Moving Average With Explanatory Variable (ARIMAX) Model: Time Series Analysis. Luo T; Zhou J; Yang J; Xie Y; Wei Y; Mai H; Lu D; Yang Y; Cui P; Ye L; Liang H; Huang J J Med Internet Res; 2023 Oct; 25():e49400. PubMed ID: 37902815 [TBL] [Abstract][Full Text] [Related]
23. 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]
24. Impact of PM Huang R; Ning H; He T; Bian G; Hu J; Xu G Environ Sci Pollut Res Int; 2019 Jun; 26(18):17974-17985. PubMed ID: 29961907 [TBL] [Abstract][Full Text] [Related]
25. Predicting machine's performance record using the stacked long short-term memory (LSTM) neural networks. Ma M; Liu C; Wei R; Liang B; Dai J J Appl Clin Med Phys; 2022 Mar; 23(3):e13558. PubMed ID: 35170838 [TBL] [Abstract][Full Text] [Related]
26. Prediction of hepatitis E using machine learning models. Guo Y; Feng Y; Qu F; Zhang L; Yan B; Lv J PLoS One; 2020; 15(9):e0237750. PubMed ID: 32941452 [TBL] [Abstract][Full Text] [Related]
27. 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]
28. Application of a combined model with seasonal autoregressive integrated moving average and support vector regression in forecasting hand-foot-mouth disease incidence in Wuhan, China. Zou JJ; Jiang GF; Xie XX; Huang J; Yang XB Medicine (Baltimore); 2019 Feb; 98(6):e14195. PubMed ID: 30732135 [TBL] [Abstract][Full Text] [Related]
29. [Analysis on association between incidence of hand foot and mouth disease and meteorological factors in Xiamen, 2013-2017]. Zhu HS; Chen S; Wang MZ; Ou JM; Xie ZH; Huang WL; Lin JW; Ye WJ Zhonghua Liu Xing Bing Xue Za Zhi; 2019 May; 40(5):531-536. PubMed ID: 31177733 [No Abstract] [Full Text] [Related]
30. Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability. Liu S; Chen J; Wang J; Wu Z; Wu W; Xu Z; Hu W; Xu F; Tong S; Shen H Int J Biometeorol; 2018 Apr; 62(4):565-574. PubMed ID: 29086082 [TBL] [Abstract][Full Text] [Related]
31. [Model of multiple seasonal autoregressive integrated moving average model and its application in prediction of the hand-foot-mouth disease incidence in Changsha]. Tan T; Chen L; Liu F Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2014 Nov; 39(11):1170-6. PubMed ID: 25432381 [TBL] [Abstract][Full Text] [Related]
32. How to improve infectious disease prediction by integrating environmental data: an application of a novel ensemble analysis strategy to predict HFMD. Tao J; Ma Y; Zhuang X; Lv Q; Liu Y; Zhang T; Yin F Epidemiol Infect; 2021 Jan; 149():e34. PubMed ID: 33446283 [TBL] [Abstract][Full Text] [Related]
33. 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]
34. The application of meteorological data and search index data in improving the prediction of HFMD: A study of two cities in Guangdong Province, China. Chen S; Liu X; Wu Y; Xu G; Zhang X; Mei S; Zhang Z; O'Meara M; O'Gara MC; Tan X; Li L Sci Total Environ; 2019 Feb; 652():1013-1021. PubMed ID: 30380469 [TBL] [Abstract][Full Text] [Related]
35. Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China. Zhao D; Zhang H; Zhang R; He S BMC Public Health; 2023 Mar; 23(1):619. PubMed ID: 37003988 [TBL] [Abstract][Full Text] [Related]
36. Different effects of meteorological factors on hand, foot and mouth disease in various climates: a spatial panel data model analysis. Wang C; Cao K; Zhang Y; Fang L; Li X; Xu Q; Huang F; Tao L; Guo J; Gao Q; Guo X BMC Infect Dis; 2016 May; 16():233. PubMed ID: 27230283 [TBL] [Abstract][Full Text] [Related]
37. Deep learning models for hepatitis E incidence prediction leveraging meteorological factors. Feng Y; Cui X; Lv J; Yan B; Meng X; Zhang L; Guo Y PLoS One; 2023; 18(3):e0282928. PubMed ID: 36913401 [TBL] [Abstract][Full Text] [Related]
38. 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]
39. Application of a hybrid ARIMA-LSTM model based on the SPEI for drought forecasting. Xu D; Zhang Q; Ding Y; Zhang D Environ Sci Pollut Res Int; 2022 Jan; 29(3):4128-4144. PubMed ID: 34403057 [TBL] [Abstract][Full Text] [Related]
40. Comparison of Predictive Models and Impact Assessment of Lockdown for COVID-19 over the United States. Makinde OS; Adeola AM; Abiodun GJ; Olusola-Makinde OO; Alejandro A J Epidemiol Glob Health; 2021 Jun; 11(2):200-207. PubMed ID: 33876598 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]