Evidence map›Paper›PMID 41582211›Full record

ArticleMicrosystems & nanoengineering2026

Ensemble-learning-assisted exhaled gas disease analysis based on in-situ construction of MOF-derived MO

Donghui Li, Weili Wang, Qi Duan, Yuxuan Wang, Hongtao Wang, Xiuli He, Guojing Wang, Weidong Wang, Hongwei Li, Dan Han and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microsystems & nanoengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Donghui LiShanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, China.
Weili WangShanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.
Qi DuanShanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, China.
Yuxuan WangShanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, China.
Hongtao WangShanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, China.
Xiuli HeState Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
Guojing WangBioengineering Research Center, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China.
Weidong WangBioengineering Research Center, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China.
Hongwei LiShanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China.
Dan HanShanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, China. handan01@tyut.edu.cn.
Shengbo SangShanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors, College of Integrated Circuits, Taiyuan University of Technology, Taiyuan, China. sunboa-sang@tyut.edu.cn.ORCID http://orcid.org/0000-0003-4974-9306

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52375572National Natural Science Foundation of China (National Science Foundation of China) 62031022
6 · The paper itself

Abstract

Human exhaled gas is rich in biomarker information that could be used for early diagnosis of disease. With the development of nanotechnology and the Internet of Medical Things (IoMT), AI-assisted nano gas sensor arrays as a non-invasive exhaled gas detection platform brings fascinating technological solutions to the field of breath detection. Herein, we designed a new heterojunction sensing array by anchoring n-GaN nanoparticles on MOF-derived p-MO

Identifiers

PMID41582211
PMCPMC12832609

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.