Evidence map›Paper›PMID 32072293›Full record

ArticleSurgical endoscopy2021

Virtual reality operating room with AI guidance: design and validation of a fire scenario.

Di Qi, Adam Ryason, Nicholas Milef, Samuel Alfred, Mohamad Rassoul Abu-Nuwar, Mojdeh Kappus, Suvranu De, Daniel B Jones

Abstract read
In one paragraph

Article in Surgical endoscopy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
  6. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Di QiCenter for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA. qid@rpi.edu.ORCID 0000-0002-0467-6628
Adam RyasonCenter for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA.
Nicholas MilefCenter for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA.
Samuel AlfredCenter for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA.
Mohamad Rassoul Abu-NuwarDepartment of Surgery, Beth Israel Deaconess Medical Center, Harvard School of Medicine, Boston, MA, USA.
Mojdeh KappusDepartment of Surgery, Beth Israel Deaconess Medical Center, Harvard School of Medicine, Boston, MA, USA.
Suvranu DeCenter for Modeling, Simulation, and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA.
Daniel B JonesDepartment of Surgery, Beth Israel Deaconess Medical Center, Harvard School of Medicine, Boston, MA, USA.

Funding

Physically Realistic Virtual SurgeryR01EB005807 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI DE, SUVRANU, JACKSON, CULLEN DAVIS · 2006 to 2024
$7.0M
Development and validation of a virtual airway skill trainer (VAST)R01HL119248 · NHLBI · RENSSELAER POLYTECHNIC INSTITUTE · PI DE, SUVRANU · 2014 to 2017
$2.9M
Development and validation of a Virtual Colorectal Surgical Trainer (VCoST)R01EB025241 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI DE, SUVRANU · 2018 to 2022
$2.7M
Developing Physics-Based Virtual Simulation Technology for Natural Orifice TranslR01EB009362 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI CAO, CAROLINE GL, DE, SUVRANU · 2011 to 2014
$2.6M
Development and Validation of a Virtual Electrosurgical Skill Trainer (VEST)R01EB014305 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI CAO, CAROLINE GL, DE, SUVRANU · 2012 to 2016
$2.5M
Developing a Virtual Basic Laparoscopic Skill Trainer (VBLaST)R01EB010037 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI CAO, CAROLINE GL, DE, SUVRANU · 2010 to 2013
$2.0M
Approach-specific, multi-GPU, multi-tool, high-realism neurosurgery simulationR44OD018334 · OD · KITWARE, INC. · PI DE, SUVRANU, ENQUOBAHRIE, ANDINET ASMAMAW · 2013 to 2015
$1.9M
Development and Validation of a Virtual Endoluminal Surgical Simulator (VESS) for Treatment of Colorectal CancerR01CA197491 · NCI · RENSSELAER POLYTECHNIC INSTITUTE · PI DE, SUVRANU · 2016 to 2019
$1.9M
NCI NIH HHS R01 CA197491NHLBI NIH HHS R01 HL119248NIBIB NIH HHS R01 EB005807NIBIB NIH HHS R01 EB009362NIBIB NIH HHS R01 EB010037NIBIB NIH HHS R01 EB014305NIBIB NIH HHS R01 EB025241NIH HHS R44 OD018334
6 · The paper itself

Abstract

backgroundOperating room (OR) fires are uncommon but disastrous events. Inappropriate handling of OR fires can result in injuries, even death. Aiming to simulate OR fire emergencies and effectively train clinicians to react appropriately, we have developed an artificial intelligence (AI)-based OR fire virtual trainer based on the principle of the "fire triangle" and SAGES FUSE curriculum. The simulator can predict the user's actions in the virtual OR and provide them with timely feedback to assist with training. We conducted a study investigating the validity of the AI-assisted OR fire trainer at the 2019 SAGES Learning Center.

methodsFifty-three participants with varying medical experience were voluntarily recruited to participate in our Institutional Review Board approved study. All participants were asked to contain a fire within the virtual OR. Participants were then asked to fill out a 7-point Likert questionnaire consisting of ten questions regarding the face validation of the AI-assisted OR fire simulator. Shapiro-Wilk tests were conducted to test normality of the scores for each trial. A Friedman's ANOVA with post hoc tests was used to evaluate the effect of multiple trials on performance.

resultsOn a 7-point scale, eight of the ten questions were rated a mean of 6 or greater (72.73%), especially those relating to the usefulness of the simulator for OR fire-containing training. 79.25% of the participants rated the degree of usefulness of AI guidance over 6 out of 7. The performance of individuals improved significantly over the five trials, χ

conclusionsThe AI-guided OR fire trainer offers the potential to assess OR personnel and teach the proper response to an iatrogenic fire scenario in a safe, repeatable, immersive environment.

Indexed as

Artificial IntelligenceFemaleFiresHumansMaleOperating RoomsValidation Studies as TopicVirtual RealityArtificial intelligenceMedical trainingOR fireValidationVirtual reality

Identifiers

PMID32072293
PMCPMC7431365

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.