283 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. 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]
5. 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]
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]
