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 *

112 related articles for article (PubMed ID: 36967890)

  • 1. Factors affecting adoption of self-service E-ticketing technology: A study on heritage sites in Bangladesh.
    Islam MN
    Heliyon; 2023 Mar; 9(3):e14691. PubMed ID: 36967890
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An empirical study of mHealth adoption in a developing country: the moderating effect of gender concern.
    Hoque MR
    BMC Med Inform Decis Mak; 2016 May; 16():51. PubMed ID: 27142844
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A holistic perspective to predict yoga tourists' revisit intention: An integration of the TPB and ECM model.
    Leou EC; Wang H
    Front Psychol; 2022; 13():1090579. PubMed ID: 36875546
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Impact of Trust and Privacy Concerns on Technology Acceptance in Healthcare: An Indian Perspective.
    Dhagarra D; Goswami M; Kumar G
    Int J Med Inform; 2020 Sep; 141():104164. PubMed ID: 32593847
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors.
    Wang H; Zhang J; Luximon Y; Qin M; Geng P; Tao D
    Int J Environ Res Public Health; 2022 Aug; 19(17):. PubMed ID: 36078473
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Investigating factors influencing the adoption of e-Health in developing countries: A patient's perspective.
    Hoque MR; Bao Y; Sorwar G
    Inform Health Soc Care; 2017 Jan; 42(1):1-17. PubMed ID: 26865037
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The impact of deontological and teleological variables on the intention to visit green hotel: The moderating role of trust.
    Haq MM; Miah M; Biswas S; Rahman SMM
    Heliyon; 2023 Apr; 9(4):e14720. PubMed ID: 37064461
    [TBL] [Abstract][Full Text] [Related]  

  • 8. How to Increase Sport Facility Users' Intention to Use AI Fitness Services: Based on the Technology Adoption Model.
    Chin JH; Do C; Kim M
    Int J Environ Res Public Health; 2022 Nov; 19(21):. PubMed ID: 36361330
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Augmenting the technology acceptance model with trust model for the initial adoption of a blockchain-based system.
    Shrestha AK; Vassileva J; Joshi S; Just J
    PeerJ Comput Sci; 2021; 7():e502. PubMed ID: 34084922
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Nexus between integrating technology readiness 2.0 index and students' e-library services adoption amid the COVID-19 challenges: Implications based on the theory of planned behavior.
    Rahmat TE; Raza S; Zahid H; Abbas J; Mohd Sobri FA; Sidiki SN
    J Educ Health Promot; 2022; 11():50. PubMed ID: 35372596
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Exploring the Influence of Determinants on Behavior Intention to Use of Multiple Media Kiosks Through Technology Readiness and Acceptance Model.
    Peng MY; Yan X
    Front Psychol; 2022; 13():852394. PubMed ID: 35432060
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Predictive factors of telemedicine service acceptance and behavioral intention of physicians.
    Rho MJ; Choi IY; Lee J
    Int J Med Inform; 2014 Aug; 83(8):559-71. PubMed ID: 24961820
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Challenges of E-Learning: Behavioral Intention of Academicians to Use E-Learning during COVID-19 Crisis.
    Khan MJ; Reddy LKV; Khan J; Narapureddy BR; Vaddamanu SK; Alhamoudi FH; Vyas R; Gurumurthy V; Altijani AAG; Chaturvedi S
    J Pers Med; 2023 Mar; 13(3):. PubMed ID: 36983736
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Determinants of Telehealth Continuance Intention: A Multi-Perspective Framework.
    Hsieh HL; Lai JM; Chuang BK; Tsai CH
    Healthcare (Basel); 2022 Oct; 10(10):. PubMed ID: 36292485
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The Use of a Technology Acceptance Model (TAM) to Predict Patients' Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability.
    Alsyouf A; Lutfi A; Alsubahi N; Alhazmi FN; Al-Mugheed K; Anshasi RJ; Alharbi NI; Albugami M
    Int J Environ Res Public Health; 2023 Jan; 20(2):. PubMed ID: 36674105
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Cultural Influence on Adoption and Use of e-Health: Evidence in Bangladesh.
    Hoque MR; Bao Y
    Telemed J E Health; 2015 Oct; 21(10):845-51. PubMed ID: 26348844
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Modeling the adoption of personal health record (PHR) among individual: the effect of health-care technology self-efficacy and gender concern.
    Dutta B; Peng MH; Sun SL
    Libyan J Med; 2018 Dec; 13(1):1500349. PubMed ID: 30037314
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model.
    Hoque R; Sorwar G
    Int J Med Inform; 2017 May; 101():75-84. PubMed ID: 28347450
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The role of farmers' green values in creation of green innovative intention and green technology adoption behavior: Evidence from farmers grain green production.
    Gao R; Zhang H; Gong C; Wu Z
    Front Psychol; 2022; 13():980570. PubMed ID: 36312093
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of the middle-aged and older users' adoption of mobile health services in China.
    Deng Z; Mo X; Liu S
    Int J Med Inform; 2014 Mar; 83(3):210-24. PubMed ID: 24388129
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.