Evidence map›Paper›PMID 36807211›Full record

ReviewLangenbeck's archives of surgery2023

Evolution of the digital operating room: the place of video technology in surgery.

Samy Cheikh Youssef, Kaled Haram, Jonathan Noël, Vipul Patel, James Porter, Prokar Dasgupta, Nadine Hachach-Haram

Abstract readReview
In one paragraph

Review in Langenbeck's archives of surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Use of Operative Video Technology in Surgical Education: A Systematic Review.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. IDEAL-compliant implementation of the DexterInnovative surgical sciences · 2025
    Article
  10. Review
  11. Article
  12. Article
  13. Surgeons versus computer vision: a comparative analysis on surgical phase recognition capabilities.International journal of computer assisted radiology and surgery · 2025
    Article
  14. Article
  15. Machine Learning-Based Automated Assessment of Intracorporeal Suturing in Laparoscopic Fundoplication.Global surgical education : journal of the Association for Surgical Education · 2025
    Article
  16. Review
  17. Article
  18. Article
  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

7 authors.

Samy Cheikh YoussefSt. Georges University of London, London, UK. samy.youssef23@gmail.com.
Kaled HaramWestminster School, London, UK.
Jonathan NoëlGuy's and St. Thomas' NHS Foundation Trust, Urology Centre, King's Health Partners, London, UK.
Vipul PatelAdventhealth Global Robotics Institute, 400 Celebration Place, Celebration, FL, USA.
James PorterDepartment of Urology, Swedish Urology Group, Seattle, WA, USA.
Prokar DasguptaGuy's and St. Thomas' NHS Foundation Trust, Urology Centre, King's Health Partners, London, UK.
Nadine Hachach-HaramDepartment of Plastic Surgery, Guy's and St. Thomas' NHS Foundation Trust, King's Health Partners, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this review was to collate current evidence wherein digitalisation, through the incorporation of video technology and artificial intelligence (AI), is being applied to the practice of surgery. Applications are vast, and the literature investigating the utility of surgical video and its synergy with AI has steadily increased over the last 2 decades. This type of technology is widespread in other industries, such as autonomy in transportation and manufacturing.

methodsArticles were identified primarily using the PubMed and MEDLINE databases. The MeSH terms used were "surgical education", "surgical video", "video labelling", "surgery", "surgical workflow", "telementoring", "telemedicine", "machine learning", "deep learning" and "operating room". Given the breadth of the subject and the scarcity of high-level data in certain areas, a narrative synthesis was selected over a meta-analysis or systematic review to allow for a focussed discussion of the topic.

resultsThree main themes were identified and analysed throughout this review, (1) the multifaceted utility of surgical video recording, (2) teleconferencing/telemedicine and (3) artificial intelligence in the operating room.

conclusionsEvidence suggests the routine collection of intraoperative data will be beneficial in the advancement of surgery, by driving standardised, evidence-based surgical care and personalised training of future surgeons. However, many barriers stand in the way of widespread implementation, necessitating close collaboration between surgeons, data scientists, medicolegal personnel and hospital policy makers.

Indexed as

Artificial IntelligenceSurgeonsHumansOperating RoomsTechnologyArtificial intelligenceRobotic surgerySurgical innovationSurgical videoVideo labelling

Identifiers

PMID36807211
PMCPMC9939374

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.