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

Classification of Illness01:17

Classification of Illness

7.6K
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...
7.6K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

417
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:
417
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

129
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
129
Multiple Regression01:25

Multiple Regression

3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
Aggregates Classification01:29

Aggregates Classification

348
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
348
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

152
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:
152

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

A hierarchical clinical fusion transformer model for personalized opioid treatment: Development and validation in diabetic surgical patients.

medRxiv : the preprint server for health sciences·2026
Same author

Generalizations of the Jaccard index and Sørensen index for assessing agreement across multiple readers in object detection and instance segmentation in biomedical imaging.

Journal of medical imaging (Bellingham, Wash.)·2026
Same author

Ethical Responsibility in the Off-Label Use of AI in Medical Imaging.

The Journal of clinical ethics·2026
Same author

Machine learning-based cardiovascular risk prediction in systemic lupus erythematosus: development and internal validation of a prognostic model.

Journal of autoimmunity·2026
Same author

Task-Based Sampling of Patient Data for Rigorous Machine Learning/AI Performance Assessment.

Journal of imaging informatics in medicine·2026
Same author

SAGE-FM: A lightweight and interpretable spatial transcriptomics foundation model.

ArXiv·2026
Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026
Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026
Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026
Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026
Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026
Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026
查看所有相关文章

相关实验视频

Updated: Jul 22, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.3K

机器学习与COVID-19的多式联络数据.

Weijie Chen1,2, Rui C Sá1,3, Yuntong Bai1,2

  • 1Medical Imaging and Data Resource Center (MIDRC), USA.

Heliyon
|July 24, 2023
PubMed
概括
此摘要是机器生成的。

这项研究审查了COVID-19的多式联机机器学习,整合了像成像和omics这样的各种数据. 它强调了使用先进的人工智能模型进行流行病准备的经验教训和未来方向.

关键词:
在 COVID-19 疫情中,机器学习是机器学习.多式联运数据多式联运数据

更多相关视频

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.8K

相关实验视频

Last Updated: Jul 22, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.3K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

4.8K

科学领域:

  • 医疗信息学 医疗信息学
  • 人工智能的人工智能
  • 公共卫生 公共卫生

背景情况:

  • 由于COVID-19的流行,人们在了解病毒性疾病方面需要快速进步.
  • 多模式数据集成为疾病分析提供了全面的方法.
  • 从癌症中的放射基因组学中吸取的经验教导了多模式策略.

研究的目的:

  • 为 COVID-19 提供最先进的多式联机机器学习概述.
  • 总结研究中调查的各种COVID-19数据模式.
  • 讨论模型评估和未来的流行病准备的发展.

主要方法:

  • 在COVID-19研究中对多式联机机器学习应用的文献综述.
  • 总结各种数据类型:临床,实验室,成像,病理学,生理学和奥米克.
  • 讨论公开可用的多式联运COVID-19数据集.

主要成果:

  • 确定了关键数据模式,包括症状,临床数据,实验室测试,成像,病理学,生理学和体质.
  • 审查了利用这些多模式数据集的机器学习发展.
  • 强调了模型评估对未来研究的重要性.

结论:

  • 多模式机器学习显示了对COVID-19理解和未来的流行病反应的重大承诺.
  • 多样化的数据源的整合对于强大的AI模型开发至关重要.
  • 持续的研究和数据共享对于在传染病管理中推进人工智能至关重要.