Assessing microvascular invasion in HBV-related hepatocellular carcinoma: an online interactive nomogram integrating inflammatory markers, radiomics, and convolutional neural networks

NLR showed a positive correlation with MRI radiomics and deep learning features. The nomogram, incorporating NLR and MRI features, accurately predicted individualized MVI risk preoperatively.

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Publication Details

Journal
Frontiers in Oncology
Published
2024-09-16
DOI
https://doi.org/10.3389/fonc.2024.1401095
Citations
8
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
3.23

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article

Assessing microvascular invasion in HBV-related hepatocellular carcinoma: an online interactive nomogram integrating inflammatory markers, radiomics, and convolutional neural networks

Lingfeng Chen, Shangeng Weng, Fadian Ding, Zhong Yun et al.
8 citations
Frontiers in Oncology
Radiomics and Machine Learning in Medical Imaging
3.23
article

Assessing microvascular invasion in HBV-related hepatocellular carcinoma: an online interactive nomogram integrating inflammatory markers, radiomics, and convolutional neural networks

Lingfeng Chen, Shangeng Weng, Fadian Ding, Zhong Yun, Xiang Zhang, W. Ou
article en
8 citations

Abstract

NLR showed a positive correlation with MRI radiomics and deep learning features. The nomogram, incorporating NLR and MRI features, accurately predicted individualized MVI risk preoperatively.

Frontiers in OncologyVol. 14
Fujian Medical University (CN), First Affiliated Hospital of Fujian Medical University (CN), Fujian Provincial Cancer Hospital (CN)
Natural Science Foundation of Fujian Province
Good health and well-being
Openalex Percentile: Top 8%
Radiomics and Machine Learning in Medical Imaging
3.23
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Assessing microvascular invasion in HBV-related hepatocellular carcinoma: an online interactive nomogram integrating inflammatory markers, radiomics, and convolutional neural networks — Lingfeng Chen, Shangeng Weng, et al. · Frontiers in Oncology (2024) | TGRS Research Map | TGRS