Quantum-enhanced hybrid feature engineering in thoracic CT image analysis for state-of-the-art nodule classification: an advanced lung cancer assessment.
- DOI
- 10.1088/2057-1976/ad4360
- Published
- 2024 May 7
- Container
- Biomedical physics & engineering express
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1088/2057-1976/ad4360,
title = {Quantum-enhanced hybrid feature engineering in thoracic CT image analysis for state-of-the-art nodule classification: an advanced lung cancer assessment.},
author = {Shivwanshi RR and Nirala N},
year = {2024},
journal = {Biomedical physics \& engineering express},
doi = {10.1088/2057-1976/ad4360},
url = {https://doi.org/10.1088/2057-1976/ad4360}
}RIS
TY - JOUR TI - Quantum-enhanced hybrid feature engineering in thoracic CT image analysis for state-of-the-art nodule classification: an advanced lung cancer assessment. AU - Shivwanshi RR AU - Nirala N PY - 2024 JO - Biomedical physics & engineering express DO - 10.1088/2057-1976/ad4360 UR - https://doi.org/10.1088/2057-1976/ad4360 ER -
APA
RR, S., & N, N. (2024). Quantum-enhanced hybrid feature engineering in thoracic CT image analysis for state-of-the-art nodule classification: an advanced lung cancer assessment.. Biomedical physics & engineering express. https://doi.org/10.1088/2057-1976/ad4360
Source records
- pubmed · retrieved 2026-09-26T05:31:35.380Z
- europe-pmc · retrieved 2026-09-26T05:31:35.394Z