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

Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

13.8K
The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
13.8K
Drug Toxicity: Risk factors01:24

Drug Toxicity: Risk factors

1
Adverse Drug Reactions (ADRs) are potential complications that arise during pharmacotherapy, influenced by multiple risk factors. Age plays a significant role; both neonates and the elderly are at heightened risk due to their respective immature and diminished metabolic and elimination processes. Gender also impacts ADRs, with females experiencing a 1.5 to 1.7-fold greater risk than males, which may be linked to pharmacokinetic, pharmacodynamic, and hormonal differences. Notably, neonates, the...
1
Free-falling Bodies: Example01:05

Free-falling Bodies: Example

32.9K
An object falling without any air resistance under the influence of gravitational force is said to be in free-fall. For free-falling bodies, the acceleration due to gravity is constant, irrespective of their mass. Free-fall is experienced not only by objects falling downward, but also by all objects whose motion is influenced by gravitational force alone. The dynamics of free-fall motion can be calculated using kinematic equations of motion, since free-fall acceleration is constant.
The...
32.9K
Review and Preview01:10

Review and Preview

8.4K
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
8.4K
Review and Preview01:13

Review and Preview

11.6K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
11.6K
Transcription Factors02:16

Transcription Factors

82.9K
Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
82.9K

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

Artificial intelligence-detected HER2 strong-positive tumor proportion predicts FISH positivity and treatment response in breast cancer.

PloS one·2026
Same author

Integrating diversity, equity, and inclusion in generative AI applications for healthcare education: a scoping review.

International journal of medical informatics·2026
Same author

Pediatric Pulmonary Infarction and Infarction-Like Pulmonary Injury: An Etiology-Oriented Narrative Review.

Seminars in thrombosis and hemostasis·2026
Same author

How crucial is research philosophy in designing an AI study in medical education?

BMC medical education·2026
Same author

The Characteristics of Training Injuries Among Chinese Competitive Rugby Sevens Players: A Retrospective Study.

Healthcare (Basel, Switzerland)·2026
Same author

Group social skill training for children on the autism spectrum: an exploratory study of a short-term program in a Chinese outpatient clinic.

International journal of developmental disabilities·2026

相关实验视频

Updated: Feb 13, 2026

Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
05:26

Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

Published on: October 25, 2024

1.8K

在基于人工智能的落风险模型中,我们是否错过了环境因素? : 一个系统的审查.

Jiyoun Song, Boeun Kim, Min-Jeoung Kang

    Research square
    |February 12, 2026
    PubMed
    概括

    人工智能 (AI) 预测秋季的模型忽视了家庭环境危害. 整合环境数据可以改善人工智能.

    科学领域:

    • 老年学是一门学科.
    • 计算机科学 计算机科学
    • 公共卫生 公共卫生

    背景情况:

    • 跌倒是老年人面临的重大风险,通常与家庭环境危害有关.
    • 环境因素是可修改的,对于防摔策略至关重要.
    • 目前的AI秋季预测模型主要关注个人因素,忽视环境影响.

    研究的目的:

    • 系统地审查环境因素的整合到基于人工智能的跌倒风险预测模型中.
    • 总结人工智能方法和预测社区老年人跌倒的表现.
    • 评估环境数据在增强人工智能落预测模型中的作用.

    主要方法:

    • 在遵守PRISMA指南的基础上进行系统审查.
    • 从创立到2025年12月,搜索了六个主要的电子数据库.
    • 包括使用人工智能模型预测老年人跌倒的研究,并纳入环境因素.

    主要成果:

    • 九项研究符合纳入标准,使用监督机器学习,计算机视觉或机器人.
    • 环境因素是多样化的,从检查清单到传感器/视觉数据.
    • 包括环境特征改善了模型歧视 (AUC-ROC 0.67-0.76) 和确定了危险.

    更多相关视频

    An R-Based Landscape Validation of a Competing Risk Model
    05:37

    An R-Based Landscape Validation of a Competing Risk Model

    Published on: September 16, 2022

    2.6K
    Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies
    10:11

    Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies

    Published on: October 22, 2014

    19.7K

    相关实验视频

    Last Updated: Feb 13, 2026

    Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
    05:26

    Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

    Published on: October 25, 2024

    1.8K
    An R-Based Landscape Validation of a Competing Risk Model
    05:37

    An R-Based Landscape Validation of a Competing Risk Model

    Published on: September 16, 2022

    2.6K
    Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies
    10:11

    Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies

    Published on: October 22, 2014

    19.7K

    结论:

    • 环境因素在当前的人工智能下降预测模型中表现不足.
    • 标准化,上下文意识的环境数据集成可以提高AI模型的相关性和预防效用.
    • 未来的研究应该专注于整合全面的环境数据,以更有效地预防跌倒.