Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system

The AIUBS-based predictive model for postoperative recurrence and metastasis in breast cancer demonstrates high predictive accuracy and clinical utility, providing valuable support for personalized treatment and follow-up decisions.

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Publication Details

Journal
American Journal of Translational Research
Published
2025-01-01
DOI
https://doi.org/10.62347/mecc4748
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system

Xiuli Cheng
1 links
American Journal of Translational Research
Radiomics and Machine Learning in Medical Imaging
article

Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system

Xiuli Cheng
article en

Abstract

The AIUBS-based predictive model for postoperative recurrence and metastasis in breast cancer demonstrates high predictive accuracy and clinical utility, providing valuable support for personalized treatment and follow-up decisions.

American Journal of Translational ResearchVol. 17(5)
Third People's Hospital of Hefei (CN)
Good health and well-being
Openalex Percentile: Top 80%
Radiomics and Machine Learning in Medical Imaging
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Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system — Xiuli Cheng · American Journal of Translational Research (2025) | TGRS Research Map | TGRS