176 related articles for article (PubMed ID: 33596871)
21. 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]
22. Spatiotemporal characteristics and the epidemiology of tuberculosis in China from 2004 to 2017 by the nationwide surveillance system.
Zuo Z; Wang M; Cui H; Wang Y; Wu J; Qi J; Pan K; Sui D; Liu P; Xu A
BMC Public Health; 2020 Aug; 20(1):1284. PubMed ID: 32843011
[TBL] [Abstract][Full Text] [Related]
23. Forecasting the incidence of acute haemorrhagic conjunctivitis in Chongqing: a time series analysis.
Qiu H; Zeng D; Yi J; Zhu H; Hu L; Jing D; Ye M
Epidemiol Infect; 2020 Aug; 148():e193. PubMed ID: 32807257
[TBL] [Abstract][Full Text] [Related]
24. [Application of multiple seasonal autoregressive integrated moving average model in predicting the mumps incidence].
Hui S; Chen L; Liu F; Ouyang Y
Zhonghua Yu Fang Yi Xue Za Zhi; 2015 Dec; 49(12):1042-6. PubMed ID: 26887296
[TBL] [Abstract][Full Text] [Related]
25. Statistical methods for predicting tuberculosis incidence based on data from Guangxi, China.
Zheng Y; Zhang L; Wang L; Rifhat R
BMC Infect Dis; 2020 Apr; 20(1):300. PubMed ID: 32321419
[TBL] [Abstract][Full Text] [Related]
26. 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]
27. 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]
28. SARFIMA model prediction for infectious diseases: application to hemorrhagic fever with renal syndrome and comparing with SARIMA.
Qi C; Zhang D; Zhu Y; Liu L; Li C; Wang Z; Li X
BMC Med Res Methodol; 2020 Sep; 20(1):243. PubMed ID: 32993517
[TBL] [Abstract][Full Text] [Related]
29. 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]
30. 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]
31. Seasonal autoregressive integrated moving average (SARIMA) time-series model for milk production forecasting in pasture-based dairy cows in the Andean highlands.
Perez-Guerra UH; Macedo R; Manrique YP; Condori EA; Gonzáles HI; Fernández E; Luque N; Pérez-Durand MG; García-Herreros M
PLoS One; 2023; 18(11):e0288849. PubMed ID: 37972120
[TBL] [Abstract][Full Text] [Related]
32. Time series analysis-based seasonal autoregressive fractionally integrated moving average to estimate hepatitis B and C epidemics in China.
Wang YB; Qing SY; Liang ZY; Ma C; Bai YC; Xu CJ
World J Gastroenterol; 2023 Nov; 29(42):5716-5727. PubMed ID: 38075851
[TBL] [Abstract][Full Text] [Related]
33. Seasonal behavior and forecasting trends of tuberculosis incidence in Holy Kerbala, Iraq.
Mohammed SH; Ahmed MM; Al-Mousawi AM; Azeez A
Int J Mycobacteriol; 2018; 7(4):361-367. PubMed ID: 30531036
[TBL] [Abstract][Full Text] [Related]
34. Predicting Seasonal Influenza Based on SARIMA Model, in Mainland China from 2005 to 2018.
Cong J; Ren M; Xie S; Wang P
Int J Environ Res Public Health; 2019 Nov; 16(23):. PubMed ID: 31783697
[TBL] [Abstract][Full Text] [Related]
35. Time series modeling of pertussis incidence in China from 2004 to 2018 with a novel wavelet based SARIMA-NAR hybrid model.
Wang Y; Xu C; Wang Z; Zhang S; Zhu Y; Yuan J
PLoS One; 2018; 13(12):e0208404. PubMed ID: 30586416
[TBL] [Abstract][Full Text] [Related]
36. 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]
37. Epidemiological features and time-series analysis of influenza incidence in urban and rural areas of Shenyang, China, 2010-2018.
Chen Y; Leng K; Lu Y; Wen L; Qi Y; Gao W; Chen H; Bai L; An X; Sun B; Wang P; Dong J
Epidemiol Infect; 2020 Feb; 148():e29. PubMed ID: 32054544
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. Prediction of visceral leishmaniasis incidence using the Seasonal Autoregressive Integrated Moving Average model (SARIMA) in the state of Maranhão, Brazil.
Pimentel KBA; Oliveira RS; Aragão CF; Aquino Júnior J; Moura MES; Guimarães-E-Silva AS; Pinheiro VCS; Gonçalves EGR; Silva AR
Braz J Biol; 2022; 84():e257402. PubMed ID: 35081217
[TBL] [Abstract][Full Text] [Related]
40. Forecasting zoonotic cutaneous leishmaniasis using meteorological factors in eastern Fars province, Iran: a SARIMA analysis.
Tohidinik HR; Mohebali M; Mansournia MA; Niakan Kalhori SR; Ali-Akbarpour M; Yazdani K
Trop Med Int Health; 2018 Aug; 23(8):860-869. PubMed ID: 29790236
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
