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

Pneumonia III: Complications and Assessment01:30

Pneumonia III: Complications and Assessment

131
Pneumonia poses the potential for numerous complications that warrant consideration. These complications include the following:
131
Pneumothorax-II01:27

Pneumothorax-II

111
Pneumothorax is a medical condition defined by the buildup of air in the pleural space between the lungs and the chest wall. This accumulation of air can lead to partial or complete lung collapse, resulting in a range of clinical manifestations. Understanding the clinical presentation and effective management strategies is crucial for healthcare professionals in providing timely and appropriate care to individuals with pneumothorax.
Clinical Manifestations:
111

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

[Analysis of clinical feature of IgG4 related disease].

Zhonghua yi xue za zhi·2016
Same author

Noninvasive measurement of renal oxygen extraction fraction under the influence of respiratory challenge.

Journal of magnetic resonance imaging : JMRI·2016
Same author

MicroRNA-103 suppresses tumor cell proliferation by targeting PDCD10 in prostate cancer.

The Prostate·2016
Same author

Clear cell carcinoma arising in previous episiotomy scar: a case report and review of the literature.

Journal of ovarian research·2016
Same author

A DNA tetrahedron-based molecular beacon for tumor-related mRNA detection in living cells.

Chemical communications (Cambridge, England)·2016
Same author

Long non-coding RNA MALAT-1 is downregulated in preeclampsia and regulates proliferation, apoptosis, migration and invasion of JEG-3 trophoblast cells.

International journal of clinical and experimental pathology·2016

相关实验视频

Updated: May 17, 2025

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
14:56

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

Published on: January 27, 2010

21.3K

使用机器学习预测肺切除术后的术后并发症:一项为期10年的研究.

Yaxuan Wang1, Shiyang Xie2, Jiayun Liu1

  • 1Department of Anesthesiology, the First Hospital of China Medical University, China.

Annals of medicine
|April 7, 2025
PubMed
概括
此摘要是机器生成的。

机器学习模型和名图可以预测肺癌手术患者的术后心血管和神经并发症 (PCNC). 这有助于早期检测和减少这些关键并发症.

关键词:
肺癌,诺莫图谱 肺癌,诺莫图机器学习 机器学习术后心血管和神经系统并发症.胸部外科手术 胸部外科手术视频辅助的胸腔镜外科手术

更多相关视频

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
Author Spotlight: A Non-Intubated Video-Assisted Thoracoscopic Surgery with Multimodal Analgesia and Sevoflurane Inhalation Anesthesia
05:39

Author Spotlight: A Non-Intubated Video-Assisted Thoracoscopic Surgery with Multimodal Analgesia and Sevoflurane Inhalation Anesthesia

Published on: May 26, 2023

1.4K

相关实验视频

Last Updated: May 17, 2025

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
14:56

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

Published on: January 27, 2010

21.3K
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
Author Spotlight: A Non-Intubated Video-Assisted Thoracoscopic Surgery with Multimodal Analgesia and Sevoflurane Inhalation Anesthesia
05:39

Author Spotlight: A Non-Intubated Video-Assisted Thoracoscopic Surgery with Multimodal Analgesia and Sevoflurane Inhalation Anesthesia

Published on: May 26, 2023

1.4K

科学领域:

  • 胸部手术研究结果研究结果
  • 计算生物学和生物信息学
  • 瘤学患者管理管理

背景情况:

  • 手术后心血管和神经复杂症 (PCNC) 显著影响胸部手术后的存活率.
  • 减少PCNC对于改善肺癌手术患者的治疗结果至关重要.

研究的目的:

  • 在接受手术的肺癌患者中确定PCNC的独立预测因子.
  • 开发和验证用于PCNC预测的机器学习模型.
  • 构建一个用于PCNC风险评估的预测名录.

主要方法:

  • 利用了16,368名肺癌手术患者的回顾性数据集.
  • 采用多个机器学习模型,包括随机森林,以进行最佳的模型选择.
  • 开发了一个预测性名录,并使用ROC,校准和决策曲线分析评估其有效性.

主要成果:

  • 确定了年龄,手术持续时间,神经阻塞,PCA,支气管阻塞剂和sufentanil作为PCNC的独立预测剂.
  • 随机森林模型显示了高准确度 (AUC 0.898培训,0.752验证).
  • 诺米图表显示出出色的预测准确性和临床适用性.

结论:

  • 机器学习模型与名ograms相结合,为早期PCNC预测提供了一个有希望的方法.
  • 这一策略可以帮助减少胸部外科手术中PCNC的发生率.
  • 开发的诺米图为风险分层和临床决策提供了有价值的工具.