相关实验视频

Updated: Jul 2, 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

诊断时肝细胞癌死亡率的预后因素:使用人工智能开发预测模型

Pablo Martínez-Blanco1, Miguel Suárez1,2,3, Sergio Gil-Rojas1

  • 1Gastroenterology Department, Virgen de la Luz Hospital, 16002 Cuenca, Spain.

Diagnostics (Basel, Switzerland)
|February 24, 2024
PubMed
概括

一个新的机器学习模型预测了肝细胞癌 (HCC) 患者在诊断时的死亡率. 该工具通过识别米兰标准和白蛋白水平等关键预后因素来帮助临床实践.

关键词:
我们的BCLCLC是BCLCLC.米兰标准是米兰标准.专辑蛋白 (albumin) 是一种肝细胞癌是肝细胞癌.机器学习是机器学习.死亡率 死亡率预后 预后 预后

更多相关视频

A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma12:24

A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma

Published on: September 30, 2021

5.2K
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis07:32

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis

Published on: April 12, 2024

1.3K

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...
346