BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1437 related articles for article (PubMed ID: 29237586)

  • 1. Using Social Media Data to Understand the Impact of Promotional Information on Laypeople's Discussions: A Case Study of Lynch Syndrome.
    Bian J; Zhao Y; Salloum RG; Guo Y; Wang M; Prosperi M; Zhang H; Du X; Ramirez-Diaz LJ; He Z; Sun Y
    J Med Internet Res; 2017 Dec; 19(12):e414. PubMed ID: 29237586
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter.
    Massey PM; Leader A; Yom-Tov E; Budenz A; Fisher K; Klassen AC
    J Med Internet Res; 2016 Dec; 18(12):e318. PubMed ID: 27919863
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Exploring Lung Cancer Screening Discussions on Twitter.
    Zhao Y; Huo J; Prosperi M; Guo Y; Li Y; Bian J
    Stud Health Technol Inform; 2019 Aug; 264():2011-2012. PubMed ID: 31438454
    [TBL] [Abstract][Full Text] [Related]  

  • 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; 22(4):e19016. PubMed ID: 32287039
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Mining Twitter to assess the determinants of health behavior toward human papillomavirus vaccination in the United States.
    Zhang H; Wheldon C; Dunn AG; Tao C; Huo J; Zhang R; Prosperi M; Guo Y; Bian J
    J Am Med Inform Assoc; 2020 Feb; 27(2):225-235. PubMed ID: 31711186
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Using Twitter to Understand the Human Bowel Disease Community: Exploratory Analysis of Key Topics.
    Pérez-Pérez M; Pérez-Rodríguez G; Fdez-Riverola F; Lourenço A
    J Med Internet Res; 2019 Aug; 21(8):e12610. PubMed ID: 31411142
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using Social Media to Characterize Public Sentiment Toward Medical Interventions Commonly Used for Cancer Screening: An Observational Study.
    Metwally O; Blumberg S; Ladabaum U; Sinha SR
    J Med Internet Res; 2017 Jun; 19(6):e200. PubMed ID: 28592395
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Communication About Hereditary Cancers on Social Media: A Content Analysis of Tweets About Hereditary Breast and Ovarian Cancer and Lynch Syndrome.
    Allen CG; Roberts M; Andersen B; Khoury MJ
    J Cancer Educ; 2020 Feb; 35(1):131-137. PubMed ID: 30506398
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Raising Awareness About Cervical Cancer Using Twitter: Content Analysis of the 2015 #SmearForSmear Campaign.
    Lenoir P; Moulahi B; Azé J; Bringay S; Mercier G; Carbonnel F
    J Med Internet Res; 2017 Oct; 19(10):e344. PubMed ID: 29038096
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Social media analytics and reachability evaluation - #Diabetes.
    Karmegam D; Mappillairaju B
    Diabetes Metab Syndr; 2022 Jan; 16(1):102359. PubMed ID: 34920205
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Identifying Sentiment of Hookah-Related Posts on Twitter.
    Allem JP; Ramanujam J; Lerman K; Chu KH; Boley Cruz T; Unger JB
    JMIR Public Health Surveill; 2017 Oct; 3(4):e74. PubMed ID: 29046267
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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; 23(10):e31101. PubMed ID: 34469327
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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; 22(10):e22624. PubMed ID: 33006937
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study.
    Sewalk KC; Tuli G; Hswen Y; Brownstein JS; Hawkins JB
    J Med Internet Res; 2018 Oct; 20(10):e10043. PubMed ID: 30314959
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis.
    Dobbs PD; Boykin AA; Ezike N; Myers AJ; Colditz JB; Primack BA
    JMIR Form Res; 2023 Aug; 7():e50346. PubMed ID: 37651169
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Pediatric Cancer Communication on Twitter: Natural Language Processing and Qualitative Content Analysis.
    Lau N; Zhao X; O'Daffer A; Weissman H; Barton K
    JMIR Cancer; 2024 May; 10():e52061. PubMed ID: 38713506
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Social Listening: A Content Analysis of E-Cigarette Discussions on Twitter.
    Cole-Lewis H; Pugatch J; Sanders A; Varghese A; Posada S; Yun C; Schwarz M; Augustson E
    J Med Internet Res; 2015 Oct; 17(10):e243. PubMed ID: 26508089
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis.
    Monselise M; Chang CH; Ferreira G; Yang R; Yang CC
    J Med Internet Res; 2021 Oct; 23(10):e30765. PubMed ID: 34581682
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study.
    Molenaar A; Lukose D; Brennan L; Jenkins EL; McCaffrey TA
    J Med Internet Res; 2024 Mar; 26():e47826. PubMed ID: 38512326
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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; 6(4):e21978. PubMed ID: 33108310
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 72.