Evidence map›Paper›PMID 38783862›Full record

ReviewFrontiers in surgery2024

Current and future applications of artificial intelligence in surgery: implications for clinical practice and research.

Miranda X Morris, Davide Fiocco, Tommaso Caneva, Paris Yiapanis, Dennis P Orgill

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Clear Vision, Clear Savings: Enhancing Efficiency in Minimally Invasive Surgery.JSLS : Journal of the Society of Laparoendoscopic Surgeons
    Pooled it
  3. Article
  4. Review
  5. Article
  6. Colour-Guided Surgery: A Conceptual Framework for Multimodal Intraoperative Visualisation-A Narrative Review.The international journal of medical robotics + computer assisted surgery : MRCAS · 2026
    Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. Experts V/S AI´s 2.0: Comparative evaluation of AI models and expert consensus in obstructive sleep apnea assessment.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Article
  18. Review
  19. Article
  20. Article
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.

Miranda X MorrisDuke University School of Medicine, Duke University Hospital, Durham, NC, United States.
Davide FioccoDepartment of Artificial Intelligence, Frontiers Media SA, Lausanne, Switzerland.
Tommaso CanevaDepartment of Artificial Intelligence, Frontiers Media SA, Lausanne, Switzerland.
Paris YiapanisDepartment of Artificial Intelligence, Frontiers Media SA, Lausanne, Switzerland.
Dennis P OrgillHarvard Medical School, Brigham and Women's Hospital, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients.

Indexed as

artificial intelligencedata sciencedeep learning—artificial intelligencemachine learningsurgery

Identifiers

PMID38783862
PMCPMC11111929

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.