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

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.2K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.2K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.6K
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...
5.6K

You might also read

Related Articles

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

Sort by
Same author

Augmented Reality in Enhancing Operating Room Crisis Checklist Adherence: Randomized Comparative Efficacy Study.

JMIR XR and spatial computing·2026
Same author

Applications of Augmented Reality for Prehospital Emergency Care: Systematic Review of Randomized Controlled Trials.

JMIR XR and spatial computing·2026
Same author

A POCUS stewardship framework for optimizing pediatric FAST in trauma: A conceptual model and evidence synthesis.

The American journal of emergency medicine·2026
Same author

Trauma-Informed Care in Emergency Ultrasound (TIES): A prospective matched patient-clinician survey study.

The American journal of emergency medicine·2026
Same author

Medicolegal Risk Assessment and Mitigation Strategies for Ultrasound-Guided Nerve Blocks in Emergency Medicine: A Risk-Focused Analysis.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine·2026
Same author

Pulmonary hypertension in cardiac tamponade: An observational cohort study of in-hospital mortality and echocardiographic findings.

The American journal of emergency medicine·2026

Related Experiment Video

Updated: Jun 5, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

502

A randomized controlled trial on evaluating clinician-supervised generative AI for decision support.

Rayan Ebnali Harari1, Abdullah Altaweel2, Tareq Ahram3

  • 1STRATUS, Mass General Brigham, Harvard Medical School, MA, USA.

International Journal of Medical Informatics
|December 4, 2024
PubMed
Summary

Supervised generative artificial intelligence (AI) significantly improved clinical decision accuracy in cardiac arrest scenarios compared to traditional methods. Clinician oversight enhances AI

Keywords:
AIChatGPTClinician supervision of AITechnology acceptanceTelemedicineTrust

More Related Videos

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

4.4K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

Related Experiment Videos

Last Updated: Jun 5, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

502
TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

4.4K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Emergency Medicine

Background:

  • Generative AI integration into telemedicine as clinical decision support systems (CDSS) offers potential for improved outcomes but is under-researched.
  • Current applications of AI in clinical decision-making, particularly in emergency scenarios, require further investigation.

Purpose of the Study:

  • To evaluate the efficacy of ChatGPT, a generative AI tool, in providing clinical guidance during cardiac arrest simulations.
  • To compare the performance, cognitive load, and trust associated with traditional paper guides, autonomous ChatGPT, and clinician-supervised ChatGPT.

Main Methods:

  • Fifty-four participants without medical backgrounds engaged in randomized controlled trials using an Augmented Reality (AR) headset for a CPR scenario.
  • Intervention groups included a paper guide, autonomous ChatGPT, and clinician-supervised ChatGPT.
  • Performance, physiological metrics (LF/HF ratio), and self-reported trust were recorded.

Main Results:

  • The clinician-supervised ChatGPT group demonstrated significantly higher decision accuracy than the paper guide and autonomous ChatGPT groups.
  • Physiological data indicated a potentially lower cognitive load in the supervised group, evidenced by a reduced LF/HF ratio.
  • Trust in AI was highest in the supervised condition, though response time was longer and autonomous AI suggested a risky option.

Conclusions:

  • Supervised generative AI shows promise for enhancing decision accuracy and user trust in emergency healthcare.
  • Clinician oversight is crucial for safe and effective AI implementation in critical care settings.
  • Further research is needed to optimize AI supervision strategies and evaluate real-world clinical implementation.