Robotics & Machine Learning Daily News2024,Issue(Jun.28) :109-110.

Guangxi Medical University Cancer Hospital Reports Findings in Support Vector Ma chines (Performance evaluation of ML models for preoperative prediction of HER2- low BC based on CE-CBBCT radiomic features: A prospective study)

广西医科大学肿瘤医院报告支持向量机研究结果(基于ce-cbct放射学特征的ML模型在HER2-低BC术前预测中的性能评价:一项前瞻性研究)

Robotics & Machine Learning Daily News2024,Issue(Jun.28) :109-110.

Guangxi Medical University Cancer Hospital Reports Findings in Support Vector Ma chines (Performance evaluation of ML models for preoperative prediction of HER2- low BC based on CE-CBBCT radiomic features: A prospective study)

广西医科大学肿瘤医院报告支持向量机研究结果(基于ce-cbct放射学特征的ML模型在HER2-低BC术前预测中的性能评价:一项前瞻性研究)

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摘要

一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新研究-支持向量机是一篇报道的主题。根据NewsRx记者在广西的新闻报道,研究表明:“探索基于增强锥形束乳腺CT(CE-CBBCT)放射组学特征的机器学习(ML)模型对人表皮生长因子受体2(HER2)-低表达乳腺癌(BC))术前预测的价值。前瞻性分析56例接受CE-CBCT治疗的HER2-negative浸润性乳腺癌患者。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning - Sup port Vector Machines is the subject of a report. According to news reporting ori ginating in Guangxi, People’s Republic of China, by NewsRx journalists, research stated, “To explore the value of machine learning (ML) models based on contrast -enhanced cone-beam breast computed tomography (CE-CBBCT) radiomics features for the preoperative prediction of human epidermal growth factor receptor 2 (HER2)- low expression breast cancer (BC). Fiftysix patients with HER2-negative invasiv e BC who underwent preoperative CE-CBBCT were prospectively analyzed.”

Key words

Guangxi/People’s Republic of China/Asi a/Machine Learning/Support Vector Machines

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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