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 Experiment Videos

DisTeam: A decision support tool for surgical team selection.

Ashkan Ebadi1, Patrick J Tighe2, Lei Zhang2

  • 1Department of Biomedical Engineering, University of Florida, 1064 Center Dr., Gainesville, FL 32611, USA.

Artificial Intelligence in Medicine
|April 2, 2017
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

COVID-Net L2C-ULTRA: An Explainable Linear-Convex Ultrasound Augmentation Learning Framework to Improve COVID-19 Assessment and Monitoring.

Sensors (Basel, Switzerland)·2024
Same author

Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis.

Sensors (Basel, Switzerland)·2023
Same author

COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound.

Sensors (Basel, Switzerland)·2023
Same author

COVIDx-US: An Open-Access Benchmark Dataset of Ultrasound Imaging Data for AI-Driven COVID-19 Analytics.

Frontiers in bioscience (Landmark edition)·2022
Same author

Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing.

Scientometrics·2020
Same author

Delirium Prediction using Machine Learning Models on Preoperative Electronic Health Records Data.

Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering·2018

A new tool, DisTeam, helps select optimal surgical teams by analyzing past performance and patient data to minimize complications. This decision support system personalizes team selection for better patient outcomes.

Area of Science:

  • Healthcare Management
  • Surgical Outcomes Research
  • Decision Support Systems

Background:

  • Surgical team composition significantly impacts patient outcomes, including complication rates.
  • Effective surgical team selection requires considering individual expertise, team synergy, and patient-specific factors.
  • Current methods for surgical team selection are often complex and may not fully optimize for patient safety.

Purpose of the Study:

  • To introduce DisTeam, a novel decision support tool for optimizing surgical team selection.
  • To develop a framework that objectively evaluates surgical teams based on historical performance and patient characteristics.
  • To personalize surgical team composition to minimize potential patient complications.

Main Methods:

  • DisTeam utilizes a metaheuristic framework for objective evaluation of surgical teams.
Keywords:
Decision supportGenetic algorithmIntra-operativeOrthopedicsPatients’ outcomeSurgical team selection

Related Experiment Videos

  • The system analyzes historical surgical team performance, including complication data and teamwork history.
  • Patient-specific data, such as age, BMI, and comorbidity index, are integrated into the team selection process.

    • Main Results:

    • DisTeam demonstrated high effectiveness in a study of 6065 orthopedic surgery cases.
    • The framework rapidly converges to optimal surgical team solutions.
    • The system provides ranked lists of personalized surgical teams, offering flexibility and alternative options.

    Conclusions:

    • DisTeam serves as a valuable decision support tool for surgical team selection.
    • The system simplifies hospital personnel scheduling by considering numerous patient and team dynamics.
    • DisTeam facilitates the creation of patient-personalized surgical teams aimed at reducing complication risks.