Evidence map›Paper›PMID 37829158›Full record

ReviewMicrosystems & nanoengineering2023

Research progress of electronic nose technology in exhaled breath disease analysis.

Ying Li, Xiangyang Wei, Yumeng Zhou, Jing Wang, Rui You

Open access · goldAbstract readReview
In one paragraph

Review in Microsystems & nanoengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
13.4field-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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 122 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Artificial Intelligence in Rhinology: A State-of-the-Art Review of Clinical Readiness and Implementation Pathways.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2026
    Review
  4. Review
  5. Sensitive and wafer-scale olfactory sensory neurons.Microsystems & nanoengineering · 2026
    Article
  6. Article
  7. Article
  8. [Advances in the application of exhaled breath analysis technology in the detection and diagnosis of liver failure].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026
    Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Review
  18. Review
  19. Adaptive Machine Learning for Electronic Nose-Based Forensic VOC Classification.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

5 authors at 2 institutions in 1 country.

Ying LiSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.
Xiangyang WeiSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.ORCID 0000-0001-6809-9455
Yumeng ZhouSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.
Jing WangSchool of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun, 130022 China.
Rui YouSchool of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.
Beijing Information Science & Technology University · CNChangchun University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages, such as convenience, safety, simplicity, and avoidance of discomfort. Based on many studies, exhaled breath analysis is a promising medical detection technology capable of diagnosing different diseases by analyzing the concentration, type and other characteristics of specific gases. In the existing gas analysis technology, the electronic nose (eNose) analysis method has great advantages of high sensitivity, rapid response, real-time monitoring, ease of use and portability. Herein, this review is intended to provide an overview of the application of human exhaled breath components in disease diagnosis, existing breath testing technologies and the development and research status of electronic nose technology. In the electronic nose technology section, the three aspects of sensors, algorithms and existing systems are summarized in detail. Moreover, the related challenges and limitations involved in the abovementioned technologies are also discussed. Finally, the conclusion and perspective of eNose technology are presented.

Indexed as

Electrical and electronic engineeringSensors

Identifiers

PMID37829158
PMCPMC10564766
OpenAlexW4387519320

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.