Computed tomography-derived radiomics models for distinguishing difficult-to-diagnose inflammatory and malignant pulmonary nodules

The nomogram model was useful in diagnosing inflammatory and malignant nodules with typical or atypical signs, especially those with malignant signs, yielding a better classification performance than the radiomics and clinical model.

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Publication Details

Journal
Biomedical Engineering and Computational Biology
Published
2025-09-01
DOI
https://doi.org/10.1177/11795972251371467
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

Computed tomography-derived radiomics models for distinguishing difficult-to-diagnose inflammatory and malignant pulmonary nodules

Xiaoyan Wang, Lili Guo, Wenli Shan, Jiao Ren et al.
Biomedical Engineering and Computational Biology
Radiomics and Machine Learning in Medical Imaging
article

Computed tomography-derived radiomics models for distinguishing difficult-to-diagnose inflammatory and malignant pulmonary nodules

Xiaoyan Wang, Lili Guo, Wenli Shan, Jiao Ren, Shaohong Wu
article en

Abstract

The nomogram model was useful in diagnosing inflammatory and malignant nodules with typical or atypical signs, especially those with malignant signs, yielding a better classification performance than the radiomics and clinical model.

Biomedical Engineering and Computational BiologyVol. 16
Nanjing Medical University (CN)
Openalex Percentile: Top 66%
Radiomics and Machine Learning in Medical Imaging
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