相关实验视频

Updated: May 15, 2025

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

8.2K

通过机器学习来预测手术方法的影响和恶性植物瘤的存活率

Gongyin Zhang1, Foyan Xu2, Lixian Wan3

  • 1Department of Breast Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, China.

Updates in surgery
|April 7, 2025
PubMed
概括

手术方法,包括乳房切除或乳房保护手术 (BCS),对乳房恶性乳腺瘤 (MPTB) 的长期存活率没有显著影响. 机器学习模型,特别是CatBoost,可以预测MPTB患者的生存结果.

关键词:
乳腺癌特定的生存率机器学习是机器学习.乳腺癌的恶性植物瘤.总体生存率 总体生存率

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

6.6K
Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography09:53

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

6.8K

相关概念视频

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
308
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
60