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

Cluster Sampling Method01:20

Cluster Sampling Method

13.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.9K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

858
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
858
Classification of Illness01:17

Classification of Illness

8.5K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.5K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

218
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
218
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

8.7K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
8.7K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.4K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.4K

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

Long-term Outcomes After Resection of Solitary Colorectal Liver Metastases.

Annals of surgical oncology·2026
Same author

Immune checkpoint inhibitor therapy after tumor-infiltrating lymphocytes in unresectable melanoma.

Journal for immunotherapy of cancer·2026
Same author

Deconvolving SARS-CoV-2 mRNA vaccine impact on immunotherapy-related survival.

Cancer discovery·2026
Same author

Diagnostic delay in histiocytic neoplasms and its association with local resource deprivation.

Haematologica·2026
Same author

ASO Visual Abstract: Long-Term Outcomes After Resection of Solitary Colorectal Liver Metastases.

Annals of surgical oncology·2026
Same author

Enhanced Telehealth in Prostate Cancer.

JAMA network open·2026
Same journal

Latent Class Log-Linear Models for Estimating Diagnostic Test Accuracy Without a Gold Standard: A Simulation Study.

Statistics in medicine·2026
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
查看所有相关文章

相关实验视频

Updated: Jan 6, 2026

A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

457

集群信息共享结构变异自编码器用于大规模医疗保健数据中缺失数据的计算.

Yasin Khadem Charvadeh1, Kenneth Seier1, Katherine S Panageas1

  • 1Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

Statistics in medicine
|December 3, 2025
PubMed
概括
此摘要是机器生成的。

我们引入了一种新方法,即集群信息共享结构变异自编码器 (CISS-VAE),以准确地归因电子健康记录 (EHR) 中缺少的数据. 这种先进的技术通过处理复杂的数据关系和各种缺失数据类型来改善医疗保健分析.

关键词:
电子健康记录是电子健康记录.缺失的数据归算缺失的数据归算.失踪并不是随机发生的.变量自动编码器变量自动编码器

更多相关视频

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

980
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K

相关实验视频

Last Updated: Jan 6, 2026

A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

457
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

980
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K

科学领域:

  • 医疗信息学 医疗信息学
  • 机器学习 机器学习
  • 生物统计学 生物统计学

背景情况:

  • 电子健康记录 (EHR) 和患者报告的结果中缺少的数据阻碍了医疗保健分析.
  • 传统的归算方法无法捕获复杂的非线性关系和各种缺失数据机制,包括缺失非随机 (MNAR).

研究的目的:

  • 开发一种先进的归算方法,有效地解决医疗分析中缺少数据的挑战.
  • 提高EHR和患者报告的结果数据的准确性和可用性,用于健康监测和分析.

主要方法:

  • 提出了集群信息共享结构变异自编码器 (CISS-VAE),这是贝叶斯神经网络模型.
  • 开发了代学习算法,以提高归算准确性和防止过拟合.
  • 通过全面的模拟和对现实世界EHR数据的应用来验证模型.

主要成果:

  • 在模拟中,CISS-VAE模型在与传统和当代归算方法相比显示出更高的准确性.
  • 该模型有效地捕捉了复杂的关联,并容纳了包括MNAR在内的各种缺失数据机制.
  • 从早期乳腺癌患者的EHR数据成功应用.

结论:

  • CISS-VAE模型提供了一个强大的解决方案,可以减轻医疗分析中缺少数据的影响.
  • 这种方法提高了使用EHR数据进行健康监测和分析的可靠性.
  • 拟议的方法通过改进数据归算技术,推动了健康信息学领域的发展.