Evidence map›Paper›PMID 39052314›Full record

ArticleJMIR formative research2024

Education in Laparoscopic Cholecystectomy: Design and Feasibility Study of the LapBot Safe Chole Mobile Game.

Mohammad Noroozi, Ace St John, Caterina Masino, Simon Laplante, Jaryd Hunter, Michael Brudno, Amin Madani, Marta Kersten-Oertel

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Mohammad NorooziApplied Perception Lab, Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada.ORCID https://orcid.org/0009-0009-3427-7693
Ace St JohnUniversity of Maryland Medical Center, Baltimore, MD, United States.ORCID https://orcid.org/0000-0001-6005-7955
Caterina MasinoSurgical Artificial Intelligence Research Academy, University Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0009-0001-7256-1750
Simon LaplanteSurgical Artificial Intelligence Research Academy, University Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6174-3287
Jaryd HunterDATA Team, University Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6501-1235
Michael BrudnoDATA Team, University Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-7947-2243
Amin MadaniSurgical Artificial Intelligence Research Academy, University Health Network, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-0901-9851
Marta Kersten-OertelApplied Perception Lab, Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada.ORCID https://orcid.org/0000-0002-9492-8402

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMajor bile duct injuries during laparoscopic cholecystectomy (LC), often stemming from errors in surgical judgment and visual misperception of critical anatomy, significantly impact morbidity, mortality, disability, and health care costs.

objectiveTo enhance safe LC learning, we developed an educational mobile game, LapBot Safe Chole, which uses an artificial intelligence (AI) model to provide real-time coaching and feedback, improving intraoperative decision-making.

methodsLapBot Safe Chole offers a free, accessible simulated learning experience with real-time AI feedback. Players engage with intraoperative LC scenarios (short video clips) and identify ideal dissection zones. After the response, users receive an accuracy score from a validated AI algorithm. The game consists of 5 levels of increasing difficulty based on the Parkland grading scale for cholecystitis.

resultsBeta testing (n=29) showed score improvements with each round, with attendings and senior trainees achieving top scores faster than junior residents. Learning curves and progression distinguished candidates, with a significant association between user level and scores (P=.003). Players found LapBot enjoyable and educational.

conclusionsLapBot Safe Chole effectively integrates safe LC principles into a fun, accessible, and educational game using AI-generated feedback. Initial beta testing supports the validity of the assessment scores and suggests high adoption and engagement potential among surgical trainees.

Indexed as

AIartificial intelligencecholecystectomydecision-makingeducationeducational gamegallbladdergamificationgamifyinteractivelaparoscopelaparoscopic cholecystectomymobile gamemobile phoneserious gamessurgery

Identifiers

PMID39052314
PMCPMC11310638

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.