[Clinical study of cervical lymph node metastasis in oral tongue squamous carcinoma by a machine learning model based on contrast-enhanced CT radiomics].

The prediction model based on enhanced CT image omics features combined with clinical parameters can effectively estimate cervical lymph node metastasis in patients with TSCC. This approach facilitates risk stratification of patients with TSCC and optimizes clinical decisions to improve treatment strategies and patient outcomes.

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Journal
PubMed
Published
2024-12-01
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

[Clinical study of cervical lymph node metastasis in oral tongue squamous carcinoma by a machine learning model based on contrast-enhanced CT radiomics].

Huaiqi Li, Jinhai Ye, Chen‐Xing Wang, Haiqiao Sun et al.
PubMed
Radiomics and Machine Learning in Medical Imaging
article

[Clinical study of cervical lymph node metastasis in oral tongue squamous carcinoma by a machine learning model based on contrast-enhanced CT radiomics].

Huaiqi Li, Jinhai Ye, Chen‐Xing Wang, Haiqiao Sun, Qinghai Zhu
article en

Abstract

The prediction model based on enhanced CT image omics features combined with clinical parameters can effectively estimate cervical lymph node metastasis in patients with TSCC. This approach facilitates risk stratification of patients with TSCC and optimizes clinical decisions to improve treatment strategies and patient outcomes.

PubMedVol. 33(6)
Nanjing Medical University (CN)
Radiomics and Machine Learning in Medical Imaging
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[Clinical study of cervical lymph node metastasis in oral tongue squamous carcinoma by a machine learning model based on contrast-enhanced CT radiomics]. — Huaiqi Li, Jinhai Ye, et al. · PubMed (2024) | TGRS Research Map | TGRS