相关实验视频

Updated: May 1, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K

机器学习模型的开发 整合病理学和临床数据 预测支淋巴结转移 乳腺癌:两中心研究

Long Wang1, Fanli Qu1, Ping Wen2

  • 1Department of Breast Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.

Cancer reports (Hoboken, N.J.)
|September 1, 2025
PubMed
概括

这项研究开发了一种基于病理学的名图,用于预测乳腺癌 (BC) 患者的下淋巴结转移 (ALNM). 它可以提高手术前预测的准确性, 帮助个性化治疗计划.

关键词:
带淋巴结转移乳腺癌机器学习编号模型病理学

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

193

相关概念视频

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
4.7K