Jove
Visualize
联系我们

相关概念视频

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Towards precision oncology: a multi-level cancer classification system integrating liquid biopsy and machine learning.

BioData mining·2025
Same author

A Multi-model Deep Learning Architecture for Diagnosing Multi-class Skin Diseases.

Journal of imaging informatics in medicine·2024
Same author

MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

BMC bioinformatics·2024
Same author

Unboxing machine learning models for concrete strength prediction using XAI.

Scientific reports·2023
Same author

Blink-To-Live eye-based communication system for users with speech impairments.

Scientific reports·2023
Same author

Computer-Assisted Image Processing System for Early Assessment of Lung Nodule Malignancy.

Cancers·2022
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jul 1, 2026

Detection of Cell-Free DNA in Blood Plasma Samples of Cancer Patients
08:25

Detection of Cell-Free DNA in Blood Plasma Samples of Cancer Patients

Published on: September 9, 2020

11.0K

精确的癌症分类使用液体活检和先进的机器学习技术.

Amr Eledkawy1, Taher Hamza1, Sara El-Metwally2,3

  • 1Department of Computer Science, Faculty of Computers and Information, Mansoura University, P.O. Box: 35516, Mansoura, Egypt.

Scientific reports
|March 11, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的液体活检方法,用于早期癌症检测,使用无血细胞DNA (cfDNA) 和蛋白质生物标志物. 该系统在检测癌症存在和分类癌症类型方面实现了高精度,改善了患者的治疗结果.

更多相关视频

A Standardized Liquid Biopsy Preanalytical Protocol for Downstream Circulating-Free DNA Applications
05:26

A Standardized Liquid Biopsy Preanalytical Protocol for Downstream Circulating-Free DNA Applications

Published on: September 16, 2022

3.9K
Automatic Separation and Collection of Cancer-Related Substances from Clinical Samples
08:49

Automatic Separation and Collection of Cancer-Related Substances from Clinical Samples

Published on: January 13, 2023

1.9K

相关实验视频

Last Updated: Jul 1, 2026

Detection of Cell-Free DNA in Blood Plasma Samples of Cancer Patients
08:25

Detection of Cell-Free DNA in Blood Plasma Samples of Cancer Patients

Published on: September 9, 2020

11.0K
A Standardized Liquid Biopsy Preanalytical Protocol for Downstream Circulating-Free DNA Applications
05:26

A Standardized Liquid Biopsy Preanalytical Protocol for Downstream Circulating-Free DNA Applications

Published on: September 16, 2022

3.9K
Automatic Separation and Collection of Cancer-Related Substances from Clinical Samples
08:49

Automatic Separation and Collection of Cancer-Related Substances from Clinical Samples

Published on: January 13, 2023

1.9K

科学领域:

  • 在瘤学瘤学.
  • 生物技术是生物技术.
  • 生物信息学是一种生物信息学.

背景情况:

  • 癌症是一个重大的全球健康挑战,强调了早期检测方法的必要性.
  • 液体活检,分析循环无细胞DNA (cfDNA/ctDNA) 和生物标志物,为非侵入性癌症诊断提供了一个有希望的途径.
  • 及时发现癌症对于改善患者生存率和实现有效治疗至关重要.

研究的目的:

  • 开发和验证用于早期癌症检测和分类的机器学习系统,使用血cfDNA/ctDNA突变和蛋白质生物标志物.
  • 通过使用先进的特征选择和分类技术,提高癌症检测的效率和准确性.

主要方法:

  • 使用相关系数和相互信息来选择特征,使用XGBoost特征重要性将数据维度减少60%.
  • 使用光梯度增强机 (LGBM) 进行分类,通过随机搜索优化超参数.
  • 组合十倍交叉验证的LGBM模型,以平衡准确度加权,用于最终预测.

主要成果:

  • 实现了99.45%的准确性和99.95%的癌症存在检测AUC.
  • 在癌症类型分类方面获得了93.94%的准确性和97.81%的AUC.
  • 显示了数据集维度的显著减少,同时保持了高的预测性能.

结论:

  • 拟议的液体活检系统在早期癌症检测和分类方面表现出高效.
  • 这种方法有可能通过及时和准确的癌症诊断来改善患者的治疗结果.
  • 结合cfDNA / ctDNA分析和蛋白质生物标记物的整合,在抗癌方面提供了强大的工具.