相关实验视频

Updated: May 24, 2025

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

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

Published on: October 10, 2018

在切除肺癌患者中,机器学习预测金融毒性

Nathaniel Deboever¹, Qasem Al-Tashi², Michael Eisenberg¹

¹Department of Thoracic and Cardiovascular Surgery, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, Texas.

Journal of the American College of Surgeons

|March 3, 2025

概括

机器学习准确地预测了肺癌患者的金融毒性 (FT). 在手术前确定有风险的个体可以进行干预,以减轻财务压力和改善生活质量.

科学领域:

在瘤学瘤学.
卫生经济学卫生经济学
数据科学数据科学数据科学

背景情况:

由于治疗费用,金融毒性 (FT) 显著影响肺癌 (LC) 患者的生活质量.
在手术前确定患有重大FT风险的患者对于及时干预至关重要.

研究的目的:

开发和验证机器学习 (ML) 模型,用于预测LC切除患者的主要FT.
在LC幸存者中确定与FT相关的关键手术前特征.

主要方法:

关于人口统计,财务和FT的调查数据从462名LC切除患者中收集.
提取了临床病理学变量,并将患者分为训练/测试组.
训练和组合了四个ML算法,优化了预测性能.

主要成果:

在接受调查的患者中,有10.0%的患者经历了严重的FT.
关键预测因素包括年龄,种族,收入,信用评分,就业状况和肺功能 (FEV1).
整体ML模型实现了高精度 (0.86),精度 (0.93) 和F1得分 (0.88).

结论:

ML模型可靠地识别具有重大FT高风险的LC患者.
术前风险分层使积极的干预措施能够管理金融毒性.
早期诊断可以改善患者的治疗结果,并减少财务负担.

更多相关视频

Pathological Analysis of Lung Metastasis Following Lateral Tail-Vein Injection of Tumor Cells

Pathological Analysis of Lung Metastasis Following Lateral Tail-Vein Injection of Tumor Cells

Published on: May 20, 2020

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

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

Published on: August 16, 2020

相关概念视频

Cancer Survival Analysis

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...