Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Machine Learning Predicts Treatment Response and Prognostic Pathways From Whole-Blood Transcriptome in Primary Biliary Cholangitis.

Liver international : official journal of the International Association for the Study of the Liver·2026
Same author

Otovent Versus Valsalva: Physiological Insights for Diagnostic and Therapeutic Autoinflation in Eustachian Tube Dysfunction.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery·2026
Same author

Pilot-Scale Evaluation of Partial-Slide Imaging for Detecting Critical Morphological Features (Excluding Parasites): Initial UK Implementation of a Hybrid Virtual-Light Microscopy Model in Haematology.

International journal of laboratory hematology·2026
Same author

Epidural anesthesia not associated with decreased 30-day surgical site infection occurrence after open colorectal surgery.

Antimicrobial stewardship & healthcare epidemiology : ASHE·2026
Same author

Analysis of Patient Presentation to the ED within 90-days of Infra-inguinal Bypass.

Annals of vascular surgery·2026
Same author

Clarifying the relationship between biomedical and health informatics and digital health: expert perspectives.

BMJ health & care informatics·2026

Related Experiment Video

Updated: Jun 8, 2026

Cryo-Electron Microscopy Screening Automation Across Multiple Grids Using Smart Leginon
07:52

Cryo-Electron Microscopy Screening Automation Across Multiple Grids Using Smart Leginon

Published on: December 1, 2023

Reaching for the cloud: on the lessons learned from grid computing technology transfer process to the biomedical

Yassene Mohammed1, Frank Dickmann, Ulrich Sax

  • 1Regional Computing Center for Lower Saxony, University of Hannover, Germany. mohammed@rrzn.uni-hannover.de

Studies in Health Technology and Informatics
|September 16, 2010
PubMed
Summary

Grid and Cloud computing transfer to life sciences faces unique challenges not covered by traditional models. Success should focus on scientific capital and opportunities, not just market impact, for better adoption.

More Related Videos

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Related Experiment Videos

Last Updated: Jun 8, 2026

Cryo-Electron Microscopy Screening Automation Across Multiple Grids Using Smart Leginon
07:52

Cryo-Electron Microscopy Screening Automation Across Multiple Grids Using Smart Leginon

Published on: December 1, 2023

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Area of Science:

  • Biomedical Informatics
  • Computational Science
  • Technology Transfer

Background:

  • Physics community pioneered computing resource sharing, leading to Grid technology.
  • Existing technology transfer models, like Bozeman's, assume technology stability, which differs from dynamic Grid and Cloud solutions.
  • Life sciences face difficulties adopting these evolving computing infrastructures.

Purpose of the Study:

  • To analyze the unique challenges in transferring Grid and Cloud computing to the life sciences.
  • To evaluate the applicability of existing technology transfer models to dynamic Grid and Cloud technologies.
  • To propose metrics for success and recommendations for improving adoption in the biomedical community.

Main Methods:

  • Analysis of technology transfer processes, comparing traditional models with the dynamic nature of Grid and Cloud computing.
  • Evaluation of difficulties encountered by the life science community in adopting these technologies.
  • Application of Bozeman's 'Effectiveness Model of Technology Transfer' to identify limitations.

Main Results:

  • Grid computing introduces transfer difficulties not addressed by Bozeman's model due to its inherent instability.
  • Traditional models are insufficient for assessing the transfer of rapidly evolving technologies like Grid and Cloud.
  • Success in healthgrids should be measured by enhanced scientific human capital and created opportunities, not solely market impact.

Conclusions:

  • The adoption of Grid and Cloud solutions in the biomedical community requires tailored approaches.
  • Recommendations are provided to improve the uptake of these technologies, addressing challenges in late funding periods.
  • Overcoming the 'vale of tears' for life science IT projects necessitates understanding and adapting transfer strategies.