Enhancing Diagnostic Accuracy in Lung Cancer: Evaluating the Performance of a Cutting-edge Artificial Intelligence Algorithm for Pulmonary Nodule Detection in Chest Radiographs.
- DOI
- 10.31661/jbpe.v0i0.2410-1838
- Published
- 2026 Dec
- Container
- Journal of biomedical physics & engineering
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.31661/jbpe.v0i0.2410-1838,
title = {Enhancing Diagnostic Accuracy in Lung Cancer: Evaluating the Performance of a Cutting-edge Artificial Intelligence Algorithm for Pulmonary Nodule Detection in Chest Radiographs.},
author = {Mehrabi M and Askari M},
year = {2026},
journal = {Journal of biomedical physics \& engineering},
doi = {10.31661/jbpe.v0i0.2410-1838},
url = {https://doi.org/10.31661/jbpe.v0i0.2410-1838}
}RIS
TY - JOUR TI - Enhancing Diagnostic Accuracy in Lung Cancer: Evaluating the Performance of a Cutting-edge Artificial Intelligence Algorithm for Pulmonary Nodule Detection in Chest Radiographs. AU - Mehrabi M AU - Askari M PY - 2026 JO - Journal of biomedical physics & engineering DO - 10.31661/jbpe.v0i0.2410-1838 UR - https://doi.org/10.31661/jbpe.v0i0.2410-1838 ER -
APA
M, M., & M, A. (2026). Enhancing Diagnostic Accuracy in Lung Cancer: Evaluating the Performance of a Cutting-edge Artificial Intelligence Algorithm for Pulmonary Nodule Detection in Chest Radiographs.. Journal of biomedical physics & engineering. https://doi.org/10.31661/jbpe.v0i0.2410-1838
Source records
- pubmed · retrieved 2026-11-10T21:01:13.057Z