The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Recent advances in biosensor for detection of lung cancer biomarkers
Abstract
Lung cancer is primary cancer threatening human life worldwide with the highest mortality rate. The early detection of lung cancer plays a critical role in the early diagnosis and subsequent treatment. However, the conventional methodologies limit the applications due to the low sensitivity, being expensive, and invasive procedure. Tumor markers as biochemical parameters can reflect cancer occurrence and progression, which show sensitivity, convenience, and low cost in developing biosensors, and act as good candidates for fabricating biosensors of detecting lung cancer. This review describes various biosensors (2013-2019) for detection of lung cancer biomarkers. Firstly, the various reported tumor markers of lung cancer are briefly described. Then, the advancements of designing biosensors for sensitive, stable, and selective identification of lung cancer biomarkers are systematically provided, with a specific focus on the main clinical biomarkers such as neuron-specific enolase (NSE), cytokeratin 19 fragment (CYFRA 21-1). Finally, the recent challenges and further opportunities for developing effective biosensors for early diagnosis of lung cancer are discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gandhi, L., Camidge, D. R., Ribeiro de Oliveira, M., Bonomi, P., Gandara, D., Khaira, D., Hann, C. L., McKeegan, E. M., Litvinovich, E., Hemken, P. M., et al. (2011) · Journal of Clinical Oncology · doi:10.1200/jco.2010.31.6208 · Cited by 603
Cited by
Tumor biomarkers for diagnosis, prognosis and targeted therapy
Zhou, Y., Tao, L., Qiu, J., Xu, J., Yang, X., Zhang, Y., Tian, X., Guan, X., Cen, X., & Zhao, Y. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01823-2 · Cited by 720
Yu, Z., Cai, G., Liu, X., & Tang, D. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.0c04501 · Cited by 282
Kumar, R., Wang, W., Kumar, J., Yang, T., Khan, A., Ali, W., & Ali, I. (2021) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2020.101812 · Cited by 172
Metadata
- Authors
- Yang, G., Xiao, Z., Tang, C., Deng, Y., Huang, H., & He, Z.
- Venue
- Biosensors and Bioelectronics
- Publisher
- Elsevier BV
- Published
- 2019-09
- Volume
- 141
- Pages
- 111416
- ISSN
- 0956-5663 (ISSN-L)
- OpenAlex
- W2950572455
- Cited by
- 330
- References
- 1
- FWCI
- 9.52
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Recent advances in biosensor for detection of lung cancer biomarkers. https://app.cochat.ai/papers/10.1016/j.bios.2019.111416
- The paper
- Yang, G., Xiao, Z., Tang, C., Deng, Y., Huang, H., & He, Z. (2019). Recent advances in biosensor for detection of lung cancer biomarkers. Biosensors and Bioelectronics. https://doi.org/10.1016/j.bios.2019.111416
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
