ReviewUpdates in surgery2024
Artificial intelligence applied to laparoscopic cholecystectomy: what is the next step? A narrative review.
Review in Updates in surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- Artificial Intelligence for Automated Recognition of Hepatocystic Anatomy During Laparoscopic Cholecystectomy: Current Evidence, Clinical Readiness, and Future Directions.Medicina (Kaunas, Lithuania) · 2026Review
- Surgeons' perceptions of artificial intelligence (AI) for gaze guidance in laparoscopic cholecystectomy.Surgical endoscopy · 2026Article
- Integrating subjective perceptions and objective video analysis to identify challenges in laparoscopic suturing: a cross-sectional study to enhance surgical training.Scientific reports · 2026Article
- A bibliometric analysis of ultrasound-based evaluation in renal transplantation.Translational andrology and urology · 2025Article
- 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 · 2025Review
- Ethical considerations on the role of artificial intelligence in defining the futility in emergency surgery.International journal of surgery (London, England) · 2025Article
- Artificial intelligence for intraoperative video analysis in robotic-assisted esophagectomy.Surgical endoscopy · 2025Review
- Gallbladder agenesis leading to an unnecessary surgery: a case report.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) is playing an increasing role in several fields of medicine. AI is also used during laparoscopic cholecystectomy (LC) surgeries. In the literature, there is no review that groups together the various fields of application of AI applied to LC. The aim of this review is to describe the use of AI in these contexts. We performed a narrative literature review by searching PubMed, Web of Science, Scopus and Embase for all studies on AI applied to LC, published from January 01, 2010, to December 30, 2023. Our focus was on randomized controlled trials (RCTs), meta-analysis, systematic reviews, and observational studies, dealing with large cohorts of patients. We then gathered further relevant studies from the reference list of the selected publications. Based on the studies reviewed, it emerges that AI could strongly improve surgical efficiency and accuracy during LC. Future prospects include speeding up, implementing, and improving the automaticity with which AI recognizes, differentiates and classifies the phases of the surgical intervention and the anatomic structures that are safe and those at risk.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.