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 *

816 related articles for article (PubMed ID: 32412418)

  • 1. Global Sentiments Surrounding the COVID-19 Pandemic on Twitter: Analysis of Twitter Trends.
    Lwin MO; Lu J; Sheldenkar A; Schulz PJ; Shin W; Gupta R; Yang Y
    JMIR Public Health Surveill; 2020 May; 6(2):e19447. PubMed ID: 32412418
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The Resurgence of Cyber Racism During the COVID-19 Pandemic and its Aftereffects: Analysis of Sentiments and Emotions in Tweets.
    Dubey AD
    JMIR Public Health Surveill; 2020 Oct; 6(4):e19833. PubMed ID: 32936772
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. The Contagion of Sentiments during the COVID-19 Pandemic Crisis: The Case of Isolation in Spain.
    Iglesias-Sánchez PP; Vaccaro Witt GF; Cabrera FE; Jambrino-Maldonado C
    Int J Environ Res Public Health; 2020 Aug; 17(16):. PubMed ID: 32824110
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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; 22(11):e20550. PubMed ID: 33119535
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence.
    Adikari A; Nawaratne R; De Silva D; Ranasinghe S; Alahakoon O; Alahakoon D
    J Med Internet Res; 2021 Apr; 23(4):e27341. PubMed ID: 33819167
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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; 22(8):e22590. PubMed ID: 32750001
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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; 22(5):e18897. PubMed ID: 32325426
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Measuring the Outreach Efforts of Public Health Authorities and the Public Response on Facebook During the COVID-19 Pandemic in Early 2020: Cross-Country Comparison.
    Sesagiri Raamkumar A; Tan SG; Wee HL
    J Med Internet Res; 2020 May; 22(5):e19334. PubMed ID: 32401219
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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; 22(8):e19629. PubMed ID: 32790641
    [TBL] [Abstract][Full Text] [Related]  

  • 12. COVID-19 Vaccine-Related Discussion on Twitter: Topic Modeling and Sentiment Analysis.
    Lyu JC; Han EL; Luli GK
    J Med Internet Res; 2021 Jun; 23(6):e24435. PubMed ID: 34115608
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study.
    Zhang C; Xu S; Li Z; Hu S
    J Med Internet Res; 2021 Mar; 23(3):e26482. PubMed ID: 33617460
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Use of Facebook by Academic Medical Centers in Taiwan During the COVID-19 Pandemic: Observational Study.
    Chu WM; Shieh GJ; Wu SL; Sheu WH
    J Med Internet Res; 2020 Nov; 22(11):e21501. PubMed ID: 33119536
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Verification in the Early Stages of the COVID-19 Pandemic: Sentiment Analysis of Japanese Twitter Users.
    Ueda R; Han F; Zhang H; Aoki T; Ogasawara K
    JMIR Infodemiology; 2024 Feb; 4():e37881. PubMed ID: 38127840
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set.
    Chen E; Lerman K; Ferrara E
    JMIR Public Health Surveill; 2020 May; 6(2):e19273. PubMed ID: 32427106
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.
    Kwok SWH; Vadde SK; Wang G
    J Med Internet Res; 2021 May; 23(5):e26953. PubMed ID: 33886492
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter.
    Xue J; Chen J; Chen C; Zheng C; Li S; Zhu T
    PLoS One; 2020; 15(9):e0239441. PubMed ID: 32976519
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Public Perceptions and Attitudes Toward COVID-19 Nonpharmaceutical Interventions Across Six Countries: A Topic Modeling Analysis of Twitter Data.
    Doogan C; Buntine W; Linger H; Brunt S
    J Med Internet Res; 2020 Sep; 22(9):e21419. PubMed ID: 32784190
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Tracking and Analyzing Public Emotion Evolutions During COVID-19: A Case Study from the Event-Driven Perspective on Microblogs.
    Li Q; Wei C; Dang J; Cao L; Liu L
    Int J Environ Res Public Health; 2020 Sep; 17(18):. PubMed ID: 32967163
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 41.