Evidence map›Paper›PMID 33552391›Full record

ReviewWorld journal of gastrointestinal surgery2021

Role of artificial intelligence in hepatobiliary and pancreatic surgery.

Hassaan Bari, Sharan Wadhwani, Bobby V M Dasari

Abstract readReview
In one paragraph

Review in World journal of gastrointestinal surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 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

22 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  14. Enhancing Tonsillectomy Recovery with AI: A Comparative Study on Postoperative Care Outcomes.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2024
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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

3 authors.

Hassaan BariDepartment of HPB and Liver Transplantation Surgery, Queen Elizabeth Hospital, Birmingham B15 2TH, United Kingdom.
Sharan WadhwaniDepartment of Radiology, Queen Elizabeth Hospital, Birmingham B15 2TH, United Kingdom.
Bobby V M DasariDepartment of HPB and Liver Transplantation Surgery, Queen Elizabeth Hospital, Birmingham B15 2TH, United Kingdom. bobby.dasari@uhb.nhs.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past decade, enhanced preoperative imaging and visualization, improved delineation of the complex anatomical structures of the liver and pancreas, and intra-operative technological advances have helped deliver the liver and pancreatic surgery with increased safety and better postoperative outcomes. Artificial intelligence (AI) has a major role to play in 3D visualization, virtual simulation, augmented reality that helps in the training of surgeons and the future delivery of conventional, laparoscopic, and robotic hepatobiliary and pancreatic (HPB) surgery; artificial neural networks and machine learning has the potential to revolutionize individualized patient care during the preoperative imaging, and postoperative surveillance. In this paper, we reviewed the existing evidence and outlined the potential for applying AI in the perioperative care of patients undergoing HPB surgery.

Indexed as

Artificial intelligenceAugmented realityIntra-operativeLiver surgeryPancreatic surgeryVirtual reality

Identifiers

PMID33552391
PMCPMC7830072

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.