相关实验视频

Updated: Jan 16, 2026

Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice
04:18

Modeling Ascending Vaginal Infection, Preterm Birth, and Neonatal Morbidity in Mice

Published on: October 10, 2025

353

使用可解释的机器学习来更好地了解早产导致的环境和社会经济贡献

Shuyu Li1, Yuqing Dai2, Ying Chen3

  • 1Department of Economics, Birmingham Business School, University of Birmingham, Birmingham, B15 2TT, UK.

Environmental pollution (Barking, Essex : 1987)
|October 4, 2025
PubMed
概括

空气污染,特别是PM2.5,显著增加了早产风险,特别是在女婴和低教育的母亲身上. 改善空气质量可以降低早产率.

关键词:
异质性的影响.预测因素是指预测因素.产前环境暴露 产前环境暴露

更多相关视频

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants11:14

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Published on: October 4, 2015

11.4K
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable09:24

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

Published on: May 17, 2024

2.1K

相关概念视频

Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.8K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
488
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
7.4K
Environmental Influences on Intelligence01:29

Environmental Influences on Intelligence

Despite the strong genetic influence on traits like intelligence, environmental factors significantly shape outcomes. For example, while over 90% of height variation is due to genetic differences, environmental factors such as nutrition also have a notable impact. Similarly, for intelligence, changes in a child's surroundings can significantly alter their IQ. Research shows that enriched environments boost children's academic success and help them develop key cognitive skills. Children...
886
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.5K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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...
245