Jove
Visualize
联系我们
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

相关概念视频

Targeted Cancer Therapies02:57

Targeted Cancer Therapies

7.5K
The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
7.5K
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

4.9K
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...
4.9K

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

Tanshinone IIA Ameliorates Heart Failure by Inhibiting Ferroptosis via the Sirt1/p53/GPX4 Signaling Pathway.

The American journal of Chinese medicine·2026
Same author

Correlation between surrogate indicators of insulin resistance and all-cause mortality in patients with severe hemorrhagic stroke: a multicenter retrospective cohort study in the United States.

Cardiovascular diabetology·2026
Same author

Advanced magnetic resonance neurography for preoperative facial nerve assessment and surgical planning in parotid tumors: a review of current evidence and surgical translation.

Frontiers in oncology·2026
Same author

MDFAT: Interactive mask decoupling and frequency-adaptive transformer for multi-focus image fusion.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

A case of normolipidemic lipoprotein glomerulopathy due to the APOE Kyoto variant.

Journal of clinical lipidology·2026
Same author

Sugarcane Biorefinery from Component Separation to High-Value Outputs: Technical Progress and Future Perspectives.

Foods (Basel, Switzerland)·2026

相关实验视频

Updated: Jun 13, 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

使用多模式学习预测BRCA突变和分层定向治疗反应:一项多中心研究.

Yi Li1,2, Xiaomin Xiong1,2, Xiaohua Liu3

  • 1School of Medicine, Chongqing University, Chongqing, China.

Annals of medicine
|September 11, 2024
PubMed
概括
此摘要是机器生成的。

这项研究开发了一种多式模式 (MIAM-C) 来预测BRCA1/2基因状态和PARPi癌症治疗患者预后. 该MIAM-C模型准确地识别了BRCA1/2突变,并改善了风险分层,以便更好地做出治疗决策.

关键词:
这就是BRCA BRCA.癌症 癌症 癌症 癌症 癌症深度学习是一种深度学习.可以解释的解释性.这是一个多式联络模式.有针对性的治疗.

更多相关视频

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

6.0K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

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

Published on: August 16, 2020

6.8K

相关实验视频

Last Updated: Jun 13, 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
Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer
07:45

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

6.0K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

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

Published on: August 16, 2020

6.8K

科学领域:

  • 在瘤学瘤学.
  • 遗传学 是一个遗传学.
  • 计算病理学计算病理学

背景情况:

  • 对于癌症治疗决策来说,BRCA1/2基因状态至关重要,但遗传检测往往无法获得.
  • 并非所有患者都能从多 (ADP-ribose) 聚合酶抑制剂 (PARPi) 中受益,因此需要改善风险分层.
  • 开发BRCA1/2状态和PARPi反应的预测模型对于个性化癌症治疗至关重要.

研究的目的:

  • 开发和验证一种多式模式模型,用于使用基因病理图像预测BRCA1/2基因状态.
  • 评估模型能够预测各种癌症类型的PARPi治疗的预后和反应的能力.
  • 为了确定与BRCA1/2突变相关的形态特征,以实现模型解释性.

主要方法:

  • 开发了一种多实例注意模型 (MIAM) 来从H&E图像中检测BRCA1/2状态.
  • 该MIAM-C模型整合了组织,细胞和临床特征,以提高预测.
  • 使用AUC和Kaplan-Meier分析评估模型的性能,在三个独立的队列 (卵巢,乳腺,前列腺,胰腺癌) 中进行了评估.

主要成果:

  • 与MIAM模型相比,MIAM-C模型在识别BRCA1/2基因型方面表现优越.
  • 高关注区域,包括高度瘤和淋巴细胞透,与BRCA1/2突变相关.
  • MIAM-C准确预测了PARPi治疗反应,并作为BRCA1/2-突变卵巢癌的独立预后因素.

结论:

  • 该MIAM-C模型从病理图像中准确检测BRCA1/2基因状态.
  • 这种多模式的方法有效地对BRCA1/2突变患者的预后进行了分层.
  • 这些发现支持AI驱动的病理分析对个性化癌症治疗的潜力.