Evidence map›Paper›PMID 35448283›Full record

ReviewBiosensors2022

Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review.

Qiwen Yu, Jing Chen, Wei Fu, Kanhar Ghulam Muhammad, Yi Li, Wenxin Liu, Linxin Xu, Hao Dong, Di Wang, Jun Liu and 2 more

Abstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Smoking behavior detection algorithm based on YOLOv8-MNC.Frontiers in computational neuroscience · 2023
    Article
  7. 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

12 authors.

Qiwen YuBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Jing ChenSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310051, China.ORCID 0000-0003-3576-7247
Wei FuBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Kanhar Ghulam MuhammadBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Yi LiBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Wenxin LiuBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Linxin XuBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Hao DongResearch Center for Sensing Materials and Devices, Zhejiang Lab, Hangzhou 311100, China.ORCID 0000-0001-8521-4937
Di WangResearch Center for Sensing Materials and Devices, Zhejiang Lab, Hangzhou 311100, China.
Jun LiuBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
Yanli LuBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.ORCID 0000-0003-4577-1936
Xing ChenBiosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.

Funding

China Postdoctoral Science Foundation 2020M681952Key Research and Development Program of Shanxi 2020ZDLSF04-03Major Scientific Project of Zhejiang Lab 2020MC0AD01National Natural Science Foundation of China 82172064Youth Science Fund Project of Zhejiang Lab 2020MC0AA04Zhejiang Provincial Natural Science Foundation LQ21F010003
6 · The paper itself

Abstract

Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indices, volatile organic compounds (VOCs), and exhaled breath condensates (EBCs), have been discovered for application in screening, diagnosis, and prognosis. However, the detection of markers still relies on bulky and professional instruments, which are limited to training personnel or laboratories. This seriously hinders population screening for early diagnosis of lung cancer. Advanced smartphones integrated with powerful applications can provide easy operation and real-time monitoring for healthcare, which demonstrates tremendous application scenarios in the biomedical analysis region from medical institutions or laboratories to personalized medicine. In this review, we propose an overview of lung-cancer-related noninvasive markers from exhaled breath, focusing on the novel development of smartphone-based platforms for the detection of these biomarkers. Lastly, we discuss the current limitations and potential solutions.

Indexed as

Lung NeoplasmsVolatile Organic CompoundsBiomarkersBiomarkers, TumorBreath TestsHumansLungSmartphoneBiomarkersBiomarkers, TumorVolatile Organic Compoundsexhaled breath condensatelung cancersmartphonevolatile organic compounds

Identifiers

PMID35448283
PMCPMC9028493

What OpenQuestion holds

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Registered trials

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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.