Evidence map›Paper›PMID 41552079›Full record

ReviewCureus2025

Role of Robotic Surgery and Artificial Intelligence in the Management of Abdominal Wall Hernias: A Systematic Review.

Dimitrios Bakaoukas, Natalia Sinou, Nikoleta Sinou, Athanassios Marinis, Dimitrios Filippou

Abstract readReview
In one paragraph

Review in Cureus, 2025. 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. Article
  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

5 authors.

Dimitrios BakaoukasDepartment of Surgery, Tzaneio Prefecture General Hospital of Piraeus, Piraeus, GRC.
Natalia SinouResearch and Education Institute in Biomedical Sciences, National and Kapodistrian University of Athens School of Medicine, Athens, GRC.
Nikoleta SinouResearch and Education Institute in Biomedical Sciences, National and Kapodistrian University of Athens School of Medicine, Athens, GRC.
Athanassios Marinis1st Department of General Surgery, Tzaneio Prefecture General Hospital of Piraeus, Piraeus, GRC.
Dimitrios FilippouDepartment of Anatomy, National and Kapodistrian University of Athens School of Medicine, Athens, GRC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Abdominal wall hernias impact millions of individuals annually. Two rapidly advancing technologies that can significantly enhance hernia management are robotic surgery, with its ergonomic features and technical benefits, and artificial intelligence, renowned for its groundbreaking computational capabilities. Robotic surgery appears to provide numerous advantages for treating both inguinal and ventral hernias, while artificial intelligence has been incorporated in various applications, indicating its potential to improve hernia repair outcomes. Nevertheless, both technologies face several challenges and limitations. A systematic review was carried out using the PubMed and Scopus databases with the search terms "robotic" AND "abdominal wall hernias" AND "artificial intelligence", resulting in 46 articles reviewed. This article examines the pros and cons of robotic surgery, explores the potential applications of artificial intelligence, and discusses the hurdles both technologies encounter. Ultimately, it concludes that although these innovations present many benefits, further high-quality research is essential, along with overcoming numerous barriers, for their effective integration into hernia repair procedures.

Indexed as

abdominal wallartificial intelligenceherniasroboticsurgery

Identifiers

PMID41552079
PMCPMC12810076

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.