Evidence map›Paper›PMID 40551095›Full record

ReviewBiomedical engineering online2025

Emerging technologies in airway management: a narrative review of intubation robotics and anatomical structure recognition algorithms.

Weixiong Chen, Yu Tian, Yingjie Wang, Lili Feng, Mannan Abdul, Shuangshuang Li, Wenxian Li, Yuan Han

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Biomedical engineering online, 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

8 authors.

Weixiong Chen *School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Yu Tian *Department of Anesthesiology, Eye & ENT Hospital of Fudan University, Shanghai, 200126, China.
Yingjie WangSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Lili FengDepartment of Anesthesiology, Eye & ENT Hospital of Fudan University, Shanghai, 200126, China.
Mannan AbdulDepartment of Anesthesiology, Eye & ENT Hospital of Fudan University, Shanghai, 200126, China.
Shuangshuang LiDepartment of Anesthesiology, Eye & ENT Hospital of Fudan University, Shanghai, 200126, China.
Wenxian LiSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China. wenxian.li@fdeent.org.
Yuan HanDepartment of Anesthesiology, Eye & ENT Hospital of Fudan University, Shanghai, 200126, China. yuan.han@fdeent.org.

Funding

China Postdoctoral Science Foundation 2023M740664Continuing Education Programs of Shanghai Medical College Fudan University FDYXYBJ-20222004grants-in-aid for scientific research from the Perioperative Airway Refinement Management Programs of the Health Human Resources Development Center, National Health Commission RCLX2315001National Natural Science Foundation of China 82201375National Natural Science Foundation of China 82271295
6 · The paper itself

Abstract

In recent years, the medical field has seen significant advancements in the field of robotics and artificial intelligence (AI). However, many healthcare professionals still find these technologies unfamiliar and complex, especially regarding their use during airway management. This review covers the current capabilities of robots and AI in tracheal intubation (TI), providing new insights that advocate for the broader adoption of these technologies to improve airway management. A literature review on robotics and AI in TI was conducted through searches in the PubMed, Web of Science, and IEEE Xplore databases. Drawing on a classification framework derived from expert opinions and existing literature, these studies are categorized into six key stages. Most of these technologies remain in the testing and validation phases, with only a few having reached commercialization. The primary goal of these robotic and AI systems is to enhance the success rate and operational efficiency of intubation while mitigating the persistent shortage of medical resources and supporting telemedicine. However, ongoing attention is required to address challenges such as high costs, a shortage of interdisciplinary talent, and ethical concerns related to medical bias and data security. Robots and AI are beginning to play a significant role in TI. Although many of these technologies remain in the theoretical stage of clinical application, their potential to enhance clinical practice is substantial, provided they are implemented as complementary tools that support rather than substitute the expertise of healthcare professionals. AI-powered robots show great potential as assistive tools for optimizing intubation maneuvers, whereas clinical decision-making (e.g., determining the necessity of intubation) remains under the supervision of physicians.

Indexed as

Airway ManagementAlgorithmsIntubation, IntratrachealRoboticsArtificial IntelligenceHumansAirway managementArtificial intelligenceRobotic endoscopyRoboticsTracheal intubation

Identifiers

PMID40551095
PMCPMC12186397

What Socratic 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 Socratic graph.