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

Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration01:28

Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration

285
Glomerular filtration rate (GFR) can be estimated from serum creatinine using the modification of diet in renal disease (MDRD) formula or the chronic kidney disease–epidemiology collaboration (CKD–EPI) equation. Both methods are widely used in clinical practice to assess kidney function and guide treatment decisions.The MDRD equation does not require weight or height measurements and is normalized to the body surface area of 1.73 m², considered the average adult surface area.
285
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

312
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
312
Dialysis01:27

Dialysis

1.7K
Renal failure occurs when the kidneys lose their ability to filter waste products from the blood effectively. It can be classified into two types: acute renal failure (ARF) and chronic renal failure (CRF).
Acute kidney injury develops suddenly and can be caused by pre-renal causes (e.g., hypovolemia, shock), intrinsic renal causes (e.g., acute tubular necrosis), or post-renal causes (e.g., urinary obstruction). In contrast, chronic renal failure progresses gradually over time and is often...
1.7K
Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

1.0K
Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
1.0K
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

329
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
329

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

[Study of electroreflectance spectrum and Franz-Keldysh effect at metal-GaAs interfaces].

Guang pu xue yu guang pu fen xi = Guang pu·2008
Same author

[Study on electro-degradation of new conjugated polymer PFO-BT15 light emitting diodes].

Guang pu xue yu guang pu fen xi = Guang pu·2008
Same author

Comparison of the curative effects of video assisted thoracoscopic anterior correction and small incision, thoracotomic anterior correction for idiopathic thoracic scoliosis.

Chinese medical journal·2008
Same author

Distribution and sources of mercury in soils from former industrialized urban areas of Beijing, China.

Environmental monitoring and assessment·2008
Same author

[Main flavonoids from Sophora flavescenes].

Yao xue xue bao = Acta pharmaceutica Sinica·2008
Same author

External validation and prediction employing the predictive squared correlation coefficient test set activity mean vs training set activity mean.

Journal of chemical information and modeling·2008

相关实验视频

Updated: Mar 7, 2026

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
13:35

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos

Published on: March 21, 2021

12.0K

开发一种可解释的机器学习模型,使用人体组成来预测初始透析患者的心血管死亡率:一项多中心研究.

Xiao-Xu Wang1, Jin-Xuan Wei2, Tian-Ke Yu2

  • 1Department of Nephrology, Qilu Hospital of Shandong University, Shandong University, Jinan, China.

Frontiers in physiology
|March 6, 2026
PubMed
概括

一个新的机器学习模型使用CT扫描来预测透析患者的心血管疾病 (CVD) 死亡. 该工具有助于早期风险评估,以便在透析开始时制定更好的预防策略.

关键词:
心血管疾病死亡率 心血管疾病死亡率透析是通过透析进行的.机器学习是机器学习.风险预测风险预测骨肌肉的密度 骨肌肉的密度

更多相关视频

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
06:48

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

2.1K
Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

704

相关实验视频

Last Updated: Mar 7, 2026

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
13:35

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos

Published on: March 21, 2021

12.0K
Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
06:48

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

Published on: June 7, 2024

2.1K
Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

704

科学领域:

  • 腎臟病學 (nephrology) 是一種醫學專業.
  • 心脏病学 心脏病学
  • 人工智能的人工智能

背景情况:

  • 心血管疾病 (CVD) 是透析患者的主要死亡原因.
  • 目前在透析开始时准确预测心血管疾病风险是有限的.

研究的目的:

  • 开发和验证一种机器学习模型,用于预测开始透析的患者中心血管疾病相关的死亡率.
  • 将计算机断层扫描 (CT) 衍生的身体组成特征集成到预测模型中.

主要方法:

  • 训练并验证了八个机器学习算法,使用临床,实验室和CT衍生体质成分数据从事件透析患者.
  • 采用特征选择技术 (逻辑回归,LASSO) 并使用歧视,校准和决策曲线分析评估模型.
  • 利用Shapley添加式解释 (SHAP) 来解释模型的解释性,并开发了一个基于网络的风险计算器.

主要成果:

  • 确定了八个关键预测因素:年龄,糖尿病,心血管疾病史,心脏干预史,透析方式,骨肌肉密度,血红蛋白和血清肌酸.
  • CatBoost模型在接收器操作特征曲线下的面积达到0.843 (内部验证) 和0.799 (外部验证).
  • SHAP分析强调了心血管疾病,骨肌肉密度和血红蛋白作为死亡率预测的重要贡献者.

结论:

  • 一个可解释的机器学习模型集成CT衍生体质组合有效地预测发生性透析患者的CVD相关死亡率.
  • 这种模式为早期风险分层和在透析开始时个性化预防干预提供了潜在的潜力.