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

Binomial Probability Distribution01:15

Binomial Probability Distribution

11.0K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
11.0K
Retrovirus Life Cycles01:10

Retrovirus Life Cycles

46.1K
Retroviruses have a single-stranded RNA genome that undergoes a special form of replication. Once the retrovirus has entered the host cell, an enzyme called reverse transcriptase synthesizes double-stranded DNA from the retroviral RNA genome. This DNA copy of the genome is then integrated into the host’s genome inside the nucleus via an enzyme called integrase. Consequently, the retroviral genome is transcribed into RNA whenever the host’s genome is transcribed, allowing the...
46.1K
Probability Histograms01:17

Probability Histograms

11.7K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
11.7K
Contingency Table01:29

Contingency Table

2.5K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.5K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

385
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:
385
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

33.8K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
33.8K

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

Trajectories of grip strength decline and risk of new-onset cardiovascular disease: evidence from the HRS and ELSA cohorts.

Frontiers in public health·2026
Same author

Refined AI-ASPECTS with modified atlas and lesion-load thresholds: advancing acute ischemic stroke imaging and prognostic prediction.

BMC medicine·2026
Same author

MicroRNA expression profiling and functional analysis of CDH3 during oogenesis in the Chinese alligator (<i>Alligator sinensis</i>).

Current zoology·2026
Same author

Innovating stents for aneurysm repair: New implant designs informed by thrombosis modeling.

Computers in biology and medicine·2026
Same author

TESTING HIGH-DIMENSIONAL REGRESSION COEFFICIENTS IN LINEAR MODELS.

Annals of statistics·2026
Same author

Value of MR high-resolution vessel wall imaging in the Moyamoya-like collateral vessels diseases at the base of the brain.

Medicine·2026

相关实验视频

Updated: Jul 13, 2025

Humanized NOD/SCID/IL2r&#947;null (hu-NSG) Mouse Model for HIV Replication and Latency Studies
07:10

Humanized NOD/SCID/IL2rγnull (hu-NSG) Mouse Model for HIV Replication and Latency Studies

Published on: January 7, 2019

15.7K

概率性艾滋病毒新发率分类 - - 没有标记的个人级别培训数据的逻辑回归.

Ben Sheng1, Changcheng Li2, Le Bao1

  • 1Department of Statistics, Penn State University, University Park, PA, USA.

The annals of applied statistics
|October 17, 2023
PubMed
概括

这项研究引入了一种新的半监督后勤回归模型,用于准确估计艾滋病毒发病率. 该模型改进了个人和综合的艾滋病毒新发症状况检测,优于目前的方法.

关键词:
艾滋病毒发病率 艾滋病毒发病率艾滋病病毒的最新发病率应急情况表 应急情况表逻辑回归的逻辑回归方法缺乏监督的学习学习.

更多相关视频

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach
07:06

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

13.4K
Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
11:10

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

12.3K

相关实验视频

Last Updated: Jul 13, 2025

Humanized NOD/SCID/IL2r&#947;null (hu-NSG) Mouse Model for HIV Replication and Latency Studies
07:10

Humanized NOD/SCID/IL2rγnull (hu-NSG) Mouse Model for HIV Replication and Latency Studies

Published on: January 7, 2019

15.7K
Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach
07:06

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

13.4K
Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
11:10

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

12.3K

科学领域:

  • 流行病学 流行病学
  • 生物统计学 生物统计学
  • 公共卫生 公共卫生

背景情况:

  • 准确的艾滋病毒发病率估计对于流行病监测和干预目标定位至关重要.
  • 基于人口的艾滋病毒影响评估 (PHIA) 调查收集了撒哈拉以南非洲地区的重要数据.
  • 区分最近和长期的艾滋病毒感染需要先进的分析方法.

研究的目的:

  • 提出一种新型的半监督后勤回归模型,用于估计个体的艾滋病毒新发病状态.
  • 整合来自PHIA调查,文学队列研究和国家流行病学模型的数据.
  • 提高艾滋病毒发病率估计在个人和总体水平的准确性.

主要方法:

  • 开发一个半监督后勤回归模型.
  • 纳入来自PHIA调查的数据 (未知最近状态).
  • 从文献队列研究 (应急表) 和国家发病率估计中整合共变量关系.

主要成果:

  • 拟议的模型在个人层面的艾滋病毒新发症状况估计中显示出更高的准确性.
  • 与二进制分类树 (BCT) 相比,该模型更适合估计汇总的艾滋病毒新发率.
  • 对马拉维的PHIA数据的应用验证了该模型的有效性.

结论:

  • 半监督后勤回归模型为艾滋病毒发病率估计提供了更准确的方法.
  • 这种方法提高了监测艾滋病毒流行病和评估预防策略的能力.
  • 该模型为高负担地区的公共卫生倡议提供了有价值的工具.