A1 Refereed original research article in a scientific journal
The role of artificial intelligence in enhancing safety assessment of laparoscopic cholecystectomy: a systematic review
Authors: El Boghdady, Michael; Temori, Shahmir; Khaireldin, Dena; Ewalds-Kvist, Béatrice M.; Ghazanfar, Mustansar A.; Aroori, Somaiah
Publisher: Elsevier BV
Publication year: 2025
Journal: Hpb
Volume: 27
ISSN: 1365-182X
DOI: https://doi.org/10.1016/j.hpb.2025.12.014
Publication's open availability at the time of reporting: No Open Access
Publication channel's open availability : No Open Access publication channel
Web address : https://doi.org/10.1016/j.hpb.2025.12.014
Abstract
BackgroundLaparoscopic cholecystectomy (LC), a common abdominal operation, is associated with significant morbidity, particularly bile duct injury. Artificial intelligence (AI) can enable real-time monitoring, assist decision-making, increase safety, and improve patient outcomes. This study systematically reviews AI applications in LC, evaluating different models and their performance.MethodsA systematic review was conducted in accordance with the PRISMA guidelines. A comprehensive literature search was conducted using PubMed and ScienceDirect databases for studies published between 2014 and 2024. All studies assessing AI applications in LC were included. Data extraction focused on the study aims, types of AI tools, datasets, anatomical recognition capabilities, and accuracy metrics.
ResultsThe search yielded 413 citations; a final list of 43 citations was compiled after applying the inclusion and exclusion criteria. Different datasets and developed AI tools were used in LC. AI tools were utilised in risk-scoring models for complication identification and outcome prediction, as well as for recognising anatomical landmarks during LC and subdividing the procedure into subtasks.ConclusionAI integration in LC is promising for improving intraoperative guidance, enhancing surgical education, and supporting decision-making processes. Future large-scale studies are warranted to validate the role of AI in improving patient safety and outcomes in LC.
BackgroundLaparoscopic cholecystectomy (LC), a common abdominal operation, is associated with significant morbidity, particularly bile duct injury. Artificial intelligence (AI) can enable real-time monitoring, assist decision-making, increase safety, and improve patient outcomes. This study systematically reviews AI applications in LC, evaluating different models and their performance.MethodsA systematic review was conducted in accordance with the PRISMA guidelines. A comprehensive literature search was conducted using PubMed and ScienceDirect databases for studies published between 2014 and 2024. All studies assessing AI applications in LC were included. Data extraction focused on the study aims, types of AI tools, datasets, anatomical recognition capabilities, and accuracy metrics.
ResultsThe search yielded 413 citations; a final list of 43 citations was compiled after applying the inclusion and exclusion criteria. Different datasets and developed AI tools were used in LC. AI tools were utilised in risk-scoring models for complication identification and outcome prediction, as well as for recognising anatomical landmarks during LC and subdividing the procedure into subtasks.ConclusionAI integration in LC is promising for improving intraoperative guidance, enhancing surgical education, and supporting decision-making processes. Future large-scale studies are warranted to validate the role of AI in improving patient safety and outcomes in LC.
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