Evidence map›Paper›PMID 36810475›Full record

ReviewMedical science monitor : international medical journal of experimental and clinical research2023

Necessity and Importance of Developing AI in Anesthesia from the Perspective of Clinical Safety and Information Security.

Bijia Song, Ming Zhou, Junchao Zhu

Open access · hybridAbstract readReview
In one paragraph

Review in Medical science monitor : international medical journal of experimental and clinical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
9.7field-weighted citation impact, top 1% of its field
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, 44 citations in OpenAlex.

  1. Trial
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  13. Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025
    Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Scope of artificial intelligence in airway management.Indian journal of anaesthesia · 2024
    Article
  20. 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

3 authors at 2 institutions in 1 country.

Bijia SongDepartment of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China (mainland).
Ming ZhouDepartment of Information, Beijing University of Technology, Beijing, China (mainland).
Junchao ZhuDepartment of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China (mainland).
China Medical University · CNBeijing University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid development of artificial intelligence (AI) technology is due to the significant progress in big data, databases, algorithms, and computing power, and medical research is a vital application direction of AI. The integrated development of AI and medicine has improved medical technology, and the efficiency of medical services and equipment has enabled doctors to better serve patients. The tasks and characteristics of the anesthesia discipline also make AI necessary for its development, and AI has also been initially applied in different fields of anesthesia. Our review aims to clarify the current situation and challenges of AI application in anesthesiology to provide clinical references and guide the future development of AI in anesthesiology. This review summarizes progress in the application of AI in perioperative risk assessment and prediction, deep monitoring and regulation of anesthesia, essential anesthesia skills operation, automatic drug administration systems, and teaching and training in anesthesia. Also discussed herein are the accompanying risks and challenges of applying AI in anesthesia: patient privacy and information security, data sources, and ethical issues, lack of capital and talent, and the "black box" phenomenon.

Indexed as

AnesthesiaAnesthesiologyAlgorithmsArtificial IntelligenceBig DataHumans

Identifiers

PMID36810475
PMCPMC9969716
OpenAlexW4316372470

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.