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.
278 related articles for article (PubMed ID: 23650546)
1. Comparative study of four time series methods in forecasting typhoid fever incidence in China. Zhang X; Liu Y; Yang M; Zhang T; Young AA; Li X PLoS One; 2013; 8(5):e63116. PubMed ID: 23650546 [TBL] [Abstract][Full Text] [Related]
2. Research on the predictive effect of a combined model of ARIMA and neural networks on human brucellosis in Shanxi Province, China: a time series predictive analysis. Zhai M; Li W; Tie P; Wang X; Xie T; Ren H; Zhang Z; Song W; Quan D; Li M; Chen L; Qiu L BMC Infect Dis; 2021 Mar; 21(1):280. PubMed ID: 33740904 [TBL] [Abstract][Full Text] [Related]
3. Forecasting deaths of road traffic injuries in China using an artificial neural network. Qian Y; Zhang X; Fei G; Sun Q; Li X; Stallones L; Xiang H Traffic Inj Prev; 2020; 21(6):407-412. PubMed ID: 32500738 [No Abstract] [Full Text] [Related]
4. ARIMA and ARIMA-ERNN models for prediction of pertussis incidence in mainland China from 2004 to 2021. Wang M; Pan J; Li X; Li M; Liu Z; Zhao Q; Luo L; Chen H; Chen S; Jiang F; Zhang L; Wang W; Wang Y BMC Public Health; 2022 Jul; 22(1):1447. PubMed ID: 35906580 [TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Development and comparison of predictive models for sexually transmitted diseases-AIDS, gonorrhea, and syphilis in China, 2011-2021. Zhu Z; Zhu X; Zhan Y; Gu L; Chen L; Li X Front Public Health; 2022; 10():966813. PubMed ID: 36091532 [TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. Prediction of reported monthly incidence of hepatitis B in Hainan Province of China based on SARIMA-BPNN model. Fang K; Cao L; Fu Z; Li W Medicine (Baltimore); 2023 Oct; 102(41):e35054. PubMed ID: 37832091 [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. Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach. Ye GH; Alim M; Guan P; Huang DS; Zhou BS; Wu W PLoS One; 2021; 16(3):e0248597. PubMed ID: 33725011 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. A Combined Model of SARIMA and Prophet Models in Forecasting AIDS Incidence in Henan Province, China. Luo Z; Jia X; Bao J; Song Z; Zhu H; Liu M; Yang Y; Shi X Int J Environ Res Public Health; 2022 May; 19(10):. PubMed ID: 35627447 [TBL] [Abstract][Full Text] [Related]
17. Time series analysis of rubella incidence in Chongqing, China using SARIMA and BPNN mathematical models. Chen Q; Zhao H; Qiu H; Wang Q; Zeng D; Ye M J Infect Dev Ctries; 2022 Aug; 16(8):1343-1350. PubMed ID: 36099379 [TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. A hybrid seasonal prediction model for tuberculosis incidence in China. Cao S; Wang F; Tam W; Tse LA; Kim JH; Liu J; Lu Z BMC Med Inform Decis Mak; 2013 May; 13():56. PubMed ID: 23638635 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]