Evidence map›Paper›PMID 39009730›Full record

ArticleSurgical endoscopy2024

LapBot-Safe Chole: validation of an artificial intelligence-powered mobile game app to teach safe cholecystectomy.

Ace St John, Muhammad Uzair Khalid, Caterina Masino, Mohammad Noroozi, Adnan Alseidi, Daniel A Hashimoto, Maria Altieri, Federico Serrot, Marta Kersten-Oertel, Amin Madani

Erratum issuedAbstract readValidation Study
PubMed Publisher
In one paragraph

Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Bile Duct Injury and Litigation in Laparoscopic Cholecystectomy: A Global Review of Current and Future Preventative Initiatives.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2025
    Review
  2. Review
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ace St JohnDepartment of Surgery, University of Maryland Medical Center, Baltimore, MD, USA.
Muhammad Uzair KhalidSurgical Artificial Intelligence Research Academy, University Health Network, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada.
Caterina MasinoSurgical Artificial Intelligence Research Academy, University Health Network, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada.
Mohammad NorooziGina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC, Canada.
Adnan AlseidiDepartment of Surgery, University of California San Francisco, San Francisco, CA, USA.
Daniel A HashimotoDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Maria AltieriDepartment of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Federico SerrotDepartment of Surgery, Emory University, Atlanta, GA, USA.
Marta Kersten-OertelGina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC, Canada.
Amin MadaniSurgical Artificial Intelligence Research Academy, University Health Network, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada. amin.madani@uhn.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGaming can serve as an educational tool to allow trainees to practice surgical decision-making in a low-stakes environment. LapBot is a novel free interactive mobile game application that uses artificial intelligence (AI) to provide players with feedback on safe dissection during laparoscopic cholecystectomy (LC). This study aims to provide validity evidence for this mobile game.

methodsTrainees and surgeons participated by downloading and playing LapBot on their smartphone. Players were presented with intraoperative LC scenes and required to locate their preferred location of dissection of the hepatocystic triangle. They received immediate accuracy scores and personalized feedback using an AI algorithm ("GoNoGoNet") that identifies safe/dangerous zones of dissection. Player scores were assessed globally and across training experience using non-parametric ANOVA. Three-month questionnaires were administered to assess the educational value of LapBot.

resultsA total of 903 participants from 64 countries played LapBot. As game difficulty increased, average scores (p < 0.0001) and confidence levels (p < 0.0001) decreased significantly. Scores were significantly positively correlated with players' case volume (p = 0.0002) and training level (p = 0.0003). Most agreed that LapBot should be incorporated as an adjunct into training programs (64.1%), as it improved their ability to reflect critically on feedback they receive during LC (47.5%) or while watching others perform LC (57.5%).

conclusionsSerious games, such as LapBot, can be effective educational tools for deliberate practice and surgical coaching by promoting learner engagement and experiential learning. Our study demonstrates that players' scores were correlated to their level of expertise, and that after playing the game, most players perceived a significant educational value.

Indexed as

Artificial IntelligenceCholecystectomy, LaparoscopicClinical CompetenceMobile ApplicationsAdultEducation, Medical, GraduateFemaleHumansInternship and ResidencyMaleVideo GamesArtificial intelligenceEducationGamificationLaparoscopic cholecystectomySerious gamesSurgery

Identifiers

PMID39009730

What OpenQuestion holds

Textmetadata
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.