Evidence map›Paper›PMID 32705406›Full record

ReviewFrontiers of medicine2020

Application of artificial intelligence in surgery.

Xiao-Yun Zhou, Yao Guo, Mali Shen, Guang-Zhong Yang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Frontiers of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 4 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

62 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. Article

2 more citing papers are in PubMed but not listed here.

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

4 authors.

Xiao-Yun ZhouThe Hamlyn Centre for Robotic Surgery, Imperial College London, London, SW7 2AZ, UK. xiaoyun.zhou14@imperial.ac.uk.
Yao GuoThe Hamlyn Centre for Robotic Surgery, Imperial College London, London, SW7 2AZ, UK.
Mali ShenThe Hamlyn Centre for Robotic Surgery, Imperial College London, London, SW7 2AZ, UK.
Guang-Zhong YangInstitute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is gradually changing the practice of surgery with technological advancements in imaging, navigation, and robotic intervention. In this article, we review the recent successful and influential applications of AI in surgery from preoperative planning and intraoperative guidance to its integration into surgical robots. We conclude this review by summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery.

Indexed as

Artificial IntelligenceRoboticsForecastingHumansartificial intelligencedeep learningmedical roboticssurgical autonomy

Identifiers

PMID32705406

What OpenQuestion holds

Textmetadata
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.