Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm

With the integration of pathological and imaging characteristics, ML algorithm can accurately predict sentinel lymph node metastasis in breast cancer patients. The RANDOM FOREST model showed ideal performance. With the incorporation of these models in the clinic, can helpful for clinicians to identify patients at risk of sentinel lymph node metastasis of breast cancer and make more reasonable treatment decisions.

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Publication Details

Journal
Discover Oncology
Published
2025-05-08
DOI
https://doi.org/10.1007/s12672-025-02493-4
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36

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article

Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm

Yongyue Wang, Qianmei Yang, Jinghuan Sun, Cuifang Liu et al.
1 citations
Discover Oncology
Radiomics and Machine Learning in Medical Imaging
1.36
article

Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm

Yongyue Wang, Qianmei Yang, Jinghuan Sun, Cuifang Liu, Guifang Dong
article en
1 citations

Abstract

With the integration of pathological and imaging characteristics, ML algorithm can accurately predict sentinel lymph node metastasis in breast cancer patients. The RANDOM FOREST model showed ideal performance. With the incorporation of these models in the clinic, can helpful for clinicians to identify patients at risk of sentinel lymph node metastasis of breast cancer and make more reasonable treatment decisions.

Discover OncologyVol. 16(1)
First People's Hospital of Chongqing (CN)
Chongqing Municipal Education Commission
Good health and well-being
Openalex Percentile: Top 21%
Radiomics and Machine Learning in Medical Imaging
1.36
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