These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

536 related articles for article (PubMed ID: 34447924)

  • 1. Analyzing Social Media to Explore the Attitudes and Behaviors Following the Announcement of Successful COVID-19 Vaccine Trials: Infodemiology Study.
    Boucher JC; Cornelson K; Benham JL; Fullerton MM; Tang T; Constantinescu C; Mourali M; Oxoby RJ; Marshall DA; Hemmati H; Badami A; Hu J; Lang R
    JMIR Infodemiology; 2021; 1(1):e28800. PubMed ID: 34447924
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Examining the Utility of Social Media in COVID-19 Vaccination: Unsupervised Learning of 672,133 Twitter Posts.
    Liew TM; Lee CS
    JMIR Public Health Surveill; 2021 Nov; 7(11):e29789. PubMed ID: 34583316
    [TBL] [Abstract][Full Text] [Related]  

  • 3. COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies.
    Muric G; Wu Y; Ferrara E
    JMIR Public Health Surveill; 2021 Nov; 7(11):e30642. PubMed ID: 34653016
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Understanding the Public's Attitudes Toward COVID-19 Vaccines in Nottinghamshire, United Kingdom: Qualitative Social Media Analysis.
    Jones LF; Bonfield S; Farrell J; Weston D
    J Med Internet Res; 2023 Mar; 25():e38404. PubMed ID: 36812390
    [TBL] [Abstract][Full Text] [Related]  

  • 5. COVID-19 Vaccine Hesitancy in Canada: Content Analysis of Tweets Using the Theoretical Domains Framework.
    Griffith J; Marani H; Monkman H
    J Med Internet Res; 2021 Apr; 23(4):e26874. PubMed ID: 33769946
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Examining Public Sentiments and Attitudes Toward COVID-19 Vaccination: Infoveillance Study Using Twitter Posts.
    Chandrasekaran R; Desai R; Shah H; Kumar V; Moustakas E
    JMIR Infodemiology; 2022; 2(1):e33909. PubMed ID: 35462735
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Change in Threads on Twitter Regarding Influenza, Vaccines, and Vaccination During the COVID-19 Pandemic: Artificial Intelligence-Based Infodemiology Study.
    Benis A; Chatsubi A; Levner E; Ashkenazi S
    JMIR Infodemiology; 2021; 1(1):e31983. PubMed ID: 34693212
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study.
    Calac AJ; Haupt MR; Li Z; Mackey T
    JMIR Infodemiology; 2022; 2(1):e33587. PubMed ID: 35320982
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Vaccine Hesitancy and Anti-Vaccination Attitudes during the Start of COVID-19 Vaccination Program: A Content Analysis on Twitter Data.
    Küçükali H; Ataç Ö; Palteki AS; Tokaç AZ; Hayran O
    Vaccines (Basel); 2022 Jan; 10(2):. PubMed ID: 35214620
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis.
    Honcharov V; Li J; Sierra M; Rivadeneira NA; Olazo K; Nguyen TT; Mackey TK; Sarkar U
    JMIR Infodemiology; 2023; 3():e40575. PubMed ID: 37113377
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets.
    Portelli B; Scaboro S; Tonino R; Chersoni E; Santus E; Serra G
    J Med Internet Res; 2022 May; 24(5):e35115. PubMed ID: 35446781
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Exploring Coronavirus Disease 2019 Vaccine Hesitancy on Twitter Using Sentiment Analysis and Natural Language Processing Algorithms.
    Bari A; Heymann M; Cohen RJ; Zhao R; Szabo L; Apas Vasandani S; Khubchandani A; DiLorenzo M; Coffee M
    Clin Infect Dis; 2022 May; 74(Suppl_3):e4-e9. PubMed ID: 35568473
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessing COVID-19 Vaccine Hesitancy, Confidence, and Public Engagement: A Global Social Listening Study.
    Hou Z; Tong Y; Du F; Lu L; Zhao S; Yu K; Piatek SJ; Larson HJ; Lin L
    J Med Internet Res; 2021 Jun; 23(6):e27632. PubMed ID: 34061757
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Artificial Intelligence-Enabled Analysis of Public Attitudes on Facebook and Twitter Toward COVID-19 Vaccines in the United Kingdom and the United States: Observational Study.
    Hussain A; Tahir A; Hussain Z; Sheikh Z; Gogate M; Dashtipour K; Ali A; Sheikh A
    J Med Internet Res; 2021 Apr; 23(4):e26627. PubMed ID: 33724919
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Dynamics of the Negative Discourse Toward COVID-19 Vaccines: Topic Modeling Study and an Annotated Data Set of Twitter Posts.
    Lindelöf G; Aledavood T; Keller B
    J Med Internet Res; 2023 Apr; 25():e41319. PubMed ID: 36877804
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Artificial Intelligence-Enabled Social Media Analysis for Pharmacovigilance of COVID-19 Vaccinations in the United Kingdom: Observational Study.
    Hussain Z; Sheikh Z; Tahir A; Dashtipour K; Gogate M; Sheikh A; Hussain A
    JMIR Public Health Surveill; 2022 May; 8(5):e32543. PubMed ID: 35144240
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis.
    Jang H; Rempel E; Roe I; Adu P; Carenini G; Janjua NZ
    J Med Internet Res; 2022 Mar; 24(3):e35016. PubMed ID: 35275835
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Attitudes of Swedish Language Twitter Users Toward COVID-19 Vaccination: Exploratory Qualitative Study.
    Beirakdar S; Klingborg L; Herzig van Wees S
    JMIR Infodemiology; 2023; 3():e42357. PubMed ID: 37012999
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Leveraging Transfer Learning to Analyze Opinions, Attitudes, and Behavioral Intentions Toward COVID-19 Vaccines: Social Media Content and Temporal Analysis.
    Liu S; Li J; Liu J
    J Med Internet Res; 2021 Aug; 23(8):e30251. PubMed ID: 34254942
    [TBL] [Abstract][Full Text] [Related]  

  • 20. The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding.
    Hagen L; Fox A; O'Leary H; Dyson D; Walker K; Lengacher CA; Hernandez R
    JMIR Infodemiology; 2022; 2(1):e34231. PubMed ID: 35814809
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 27.