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Items: 1 to 20 of 112

2.

A review of influenza detection and prediction through social networking sites.

Alessa A, Faezipour M.

Theor Biol Med Model. 2018 Feb 1;15(1):2. doi: 10.1186/s12976-017-0074-5. Review.

3.

Analysing Twitter and web queries for flu trend prediction.

Santos JC, Matos S.

Theor Biol Med Model. 2014 May 7;11 Suppl 1:S6. doi: 10.1186/1742-4682-11-S1-S6. Epub 2014 May 7.

4.

Twitter-Based Influenza Detection After Flu Peak via Tweets With Indirect Information: Text Mining Study.

Wakamiya S, Kawai Y, Aramaki E.

JMIR Public Health Surveill. 2018 Sep 25;4(3):e65. doi: 10.2196/publichealth.8627.

5.

Using twitter to examine smoking behavior and perceptions of emerging tobacco products.

MyslĂ­n M, Zhu SH, Chapman W, Conway M.

J Med Internet Res. 2013 Aug 29;15(8):e174. doi: 10.2196/jmir.2534.

6.

Improved Real-Time Influenza Surveillance: Using Internet Search Data in Eight Latin American Countries.

Clemente L, Lu F, Santillana M.

JMIR Public Health Surveill. 2019 Apr 4;5(2):e12214. doi: 10.2196/12214.

7.

A case study of the New York City 2012-2013 influenza season with daily geocoded Twitter data from temporal and spatiotemporal perspectives.

Nagar R, Yuan Q, Freifeld CC, Santillana M, Nojima A, Chunara R, Brownstein JS.

J Med Internet Res. 2014 Oct 20;16(10):e236. doi: 10.2196/jmir.3416.

8.

ID-Viewer: a visual analytics architecture for infectious diseases surveillance and response management in Pakistan.

Ali MA, Ahsan Z, Amin M, Latif S, Ayyaz A, Ayyaz MN.

Public Health. 2016 May;134:72-85. doi: 10.1016/j.puhe.2016.01.006. Epub 2016 Feb 13.

PMID:
26880489
9.

The reliability of tweets as a supplementary method of seasonal influenza surveillance.

Aslam AA, Tsou MH, Spitzberg BH, An L, Gawron JM, Gupta DK, Peddecord KM, Nagel AC, Allen C, Yang JA, Lindsay S.

J Med Internet Res. 2014 Nov 14;16(11):e250. doi: 10.2196/jmir.3532.

10.

Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data.

Kagashe I, Yan Z, Suheryani I.

J Med Internet Res. 2017 Sep 12;19(9):e315. doi: 10.2196/jmir.7393.

11.

The complex relationship of realspace events and messages in cyberspace: case study of influenza and pertussis using tweets.

Nagel AC, Tsou MH, Spitzberg BH, An L, Gawron JM, Gupta DK, Yang JA, Han S, Peddecord KM, Lindsay S, Sawyer MH.

J Med Internet Res. 2013 Oct 24;15(10):e237. doi: 10.2196/jmir.2705.

12.

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning.

Cole-Lewis H, Varghese A, Sanders A, Schwarz M, Pugatch J, Augustson E.

J Med Internet Res. 2015 Aug 25;17(8):e208. doi: 10.2196/jmir.4392.

13.

An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages.

Tuarob S, Tucker CS, Salathe M, Ram N.

J Biomed Inform. 2014 Jun;49:255-68. doi: 10.1016/j.jbi.2014.03.005. Epub 2014 Mar 16.

14.

Using electronic health records and Internet search information for accurate influenza forecasting.

Yang S, Santillana M, Brownstein JS, Gray J, Richardson S, Kou SC.

BMC Infect Dis. 2017 May 8;17(1):332. doi: 10.1186/s12879-017-2424-7.

15.

FluBreaks: early epidemic detection from Google flu trends.

Pervaiz F, Pervaiz M, Abdur Rehman N, Saif U.

J Med Internet Res. 2012 Oct 4;14(5):e125. doi: 10.2196/jmir.2102.

16.

"When 'Bad' is 'Good'": Identifying Personal Communication and Sentiment in Drug-Related Tweets.

Daniulaityte R, Chen L, Lamy FR, Carlson RG, Thirunarayan K, Sheth A.

JMIR Public Health Surveill. 2016 Oct 24;2(2):e162.

17.

Automatic classification of diseases from free-text death certificates for real-time surveillance.

Koopman B, Karimi S, Nguyen A, McGuire R, Muscatello D, Kemp M, Truran D, Zhang M, Thackway S.

BMC Med Inform Decis Mak. 2015 Jul 15;15:53. doi: 10.1186/s12911-015-0174-2.

18.

Twitter Influenza Surveillance: Quantifying Seasonal Misdiagnosis Patterns and their Impact on Surveillance Estimates.

Mowery J.

Online J Public Health Inform. 2016 Dec 28;8(3):e198. doi: 10.5210/ojphi.v8i3.7011. eCollection 2016.

19.

Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza.

Allen C, Tsou MH, Aslam A, Nagel A, Gawron JM.

PLoS One. 2016 Jul 25;11(7):e0157734. doi: 10.1371/journal.pone.0157734. eCollection 2016.

20.

Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models.

Du J, Tang L, Xiang Y, Zhi D, Xu J, Song HY, Tao C.

J Med Internet Res. 2018 Jul 9;20(7):e236. doi: 10.2196/jmir.9413.

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