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Journal Abstract Search

938 related items for PubMed ID: 32490846

  • 1. Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study.
    Mackey T, Purushothaman V, Li J, Shah N, Nali M, Bardier C, Liang B, Cai M, Cuomo R.
    JMIR Public Health Surveill; 2020 Jun 08; 6(2):e19509. PubMed ID: 32490846
    [Abstract] [Full Text] [Related]

  • 2. Big Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram.
    Mackey TK, Li J, Purushothaman V, Nali M, Shah N, Bardier C, Cai M, Liang B.
    JMIR Public Health Surveill; 2020 Aug 25; 6(3):e20794. PubMed ID: 32750006
    [Abstract] [Full Text] [Related]

  • 3. Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.
    Shen C, Chen A, Luo C, Zhang J, Feng B, Liao W.
    J Med Internet Res; 2020 May 28; 22(5):e19421. PubMed ID: 32452804
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  • 4. Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.
    Abd-Alrazaq A, Alhuwail D, Househ M, Hamdi M, Shah Z.
    J Med Internet Res; 2020 Apr 21; 22(4):e19016. PubMed ID: 32287039
    [Abstract] [Full Text] [Related]

  • 5. Identification and characterization of tweets related to the 2015 Indiana HIV outbreak: A retrospective infoveillance study.
    Cai M, Shah N, Li J, Chen WH, Cuomo RE, Obradovich N, Mackey TK.
    PLoS One; 2020 Apr 21; 15(8):e0235150. PubMed ID: 32845882
    [Abstract] [Full Text] [Related]

  • 6. Topics, Trends, and Sentiments of Tweets About the COVID-19 Pandemic: Temporal Infoveillance Study.
    Chandrasekaran R, Mehta V, Valkunde T, Moustakas E.
    J Med Internet Res; 2020 Oct 23; 22(10):e22624. PubMed ID: 33006937
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  • 7. Temporal and Location Variations, and Link Categories for the Dissemination of COVID-19-Related Information on Twitter During the SARS-CoV-2 Outbreak in Europe: Infoveillance Study.
    Pobiruchin M, Zowalla R, Wiesner M.
    J Med Internet Res; 2020 Aug 28; 22(8):e19629. PubMed ID: 32790641
    [Abstract] [Full Text] [Related]

  • 8. Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence.
    Hung M, Lauren E, Hon ES, Birmingham WC, Xu J, Su S, Hon SD, Park J, Dang P, Lipsky MS.
    J Med Internet Res; 2020 Aug 18; 22(8):e22590. PubMed ID: 32750001
    [Abstract] [Full Text] [Related]

  • 9. COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.
    Ahmed W, Vidal-Alaball J, Downing J, López Seguí F.
    J Med Internet Res; 2020 May 06; 22(5):e19458. PubMed ID: 32352383
    [Abstract] [Full Text] [Related]

  • 10. Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach.
    Xue J, Chen J, Hu R, Chen C, Zheng C, Su Y, Zhu T.
    J Med Internet Res; 2020 Nov 25; 22(11):e20550. PubMed ID: 33119535
    [Abstract] [Full Text] [Related]

  • 11. Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea.
    Park HW, Park S, Chong M.
    J Med Internet Res; 2020 May 05; 22(5):e18897. PubMed ID: 32325426
    [Abstract] [Full Text] [Related]

  • 12. Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access.
    Mackey T, Kalyanam J, Klugman J, Kuzmenko E, Gupta R.
    J Med Internet Res; 2018 Apr 27; 20(4):e10029. PubMed ID: 29613851
    [Abstract] [Full Text] [Related]

  • 13. The Hidden Pandemic of Family Violence During COVID-19: Unsupervised Learning of Tweets.
    Xue J, Chen J, Chen C, Hu R, Zhu T.
    J Med Internet Res; 2020 Nov 06; 22(11):e24361. PubMed ID: 33108315
    [Abstract] [Full Text] [Related]

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  • 16. Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study.
    Boon-Itt S, Skunkan Y.
    JMIR Public Health Surveill; 2020 Nov 11; 6(4):e21978. PubMed ID: 33108310
    [Abstract] [Full Text] [Related]

  • 17. Identification of Risk Factors and Symptoms of COVID-19: Analysis of Biomedical Literature and Social Media Data.
    Jeon J, Baruah G, Sarabadani S, Palanica A.
    J Med Internet Res; 2020 Oct 02; 22(10):e20509. PubMed ID: 32936770
    [Abstract] [Full Text] [Related]

  • 18. Mining Physicians' Opinions on Social Media to Obtain Insights Into COVID-19: Mixed Methods Analysis.
    Wahbeh A, Nasralah T, Al-Ramahi M, El-Gayar O.
    JMIR Public Health Surveill; 2020 Jun 18; 6(2):e19276. PubMed ID: 32421686
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  • 20. Using Twitter Comments to Understand People's Experiences of UK Health Care During the COVID-19 Pandemic: Thematic and Sentiment Analysis.
    Ainley E, Witwicki C, Tallett A, Graham C.
    J Med Internet Res; 2021 Oct 25; 23(10):e31101. PubMed ID: 34469327
    [Abstract] [Full Text] [Related]

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