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

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

105
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:
105
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.6K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.6K

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

Multimodal genomic prediction is not a buzzword: why modern plant breeding must integrate genomics, enviromics, and phenomics.

G3 (Bethesda, Md.)·2026
Same author

Comparing statistical 'phenomic prediction' models for remote-sensing-based phenotyping of maize susceptibility to common rust.

Plant phenomics (Washington, D.C.)·2026
Same author

Pharmacological treatment patterns, factors associated with glycemic control, and renal function parameters in a real-world cohort of Hispanic adults with type 2 diabetes.

Biomedical reports·2026
Same author

Multimodal deep learning improves cross-environment prediction of durum wheat yield components.

BMC plant biology·2026
Same author

Nonlinear genomic selection index accelerates multi-trait crop improvement.

Nature communications·2026
Same author

Bayesian neural networks for genomic prediction: uncertainty quantification and SNP interpretation with SHAP and GWAS.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2026

相关实验视频

Updated: May 31, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.4K

使用机器学习预测老年人住院的情况.

Raymundo Buenrostro-Mariscal1, Osval A Montesinos-López1, Cesar Gonzalez-Gonzalez1

  • 1School of Telematics, University of Colima, Colima 28040, Mexico.

Geriatrics (Basel, Switzerland)
|January 23, 2025
PubMed
概括
此摘要是机器生成的。

预测老年人住院的情况至关重要. 一个随机森林模型确定了功能限制,年龄和脑血管事故作为关键预测因素,有助于医疗保健资源分配.

关键词:
健康预测健康预测住院治疗 住院治疗机器学习是机器学习.年龄较大的成年人.随机的森林随机的森林

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

8.2K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

相关实验视频

Last Updated: May 31, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.4K
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

8.2K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

科学领域:

  • 老年学是指老年学的学科.
  • 公共卫生 公共卫生
  • 数据科学数据科学数据科学

背景情况:

  • 墨西哥老年人住院率正在上升,原因是慢性疾病和紧张的医疗保健资源.
  • 墨西哥健康与衰老研究 (MHAS) 提供了对理解住院趋势至关重要的纵向数据.

研究的目的:

  • 使用随机森林 (RF) 算法,开发老年人住院预测模型.
  • 通过分析变量重要性来确定住院的关键预测因素.

主要方法:

  • 开发并使用各种数据分区策略和变量交互来评估RF模型.
  • 修改后的嵌套交叉验证确保了模型的稳定性,使用灵敏度,特异性和kappa系数作为评估指标.
  • 使用杂质和变重要性平均下降来评估变量重要性.

主要成果:

  • 最佳模型 (ST2与相互作用和20%的测试比例) 实现了0.7215的灵敏度和0.4935.5的特异性.
  • 关键预测因素包括功能限制 (31.1%),年龄 (12.75%),脑血管事故史 (12.4%) 和教育水平 (12.08%).
  • 该模型有效地捕捉了健康和社会经济因素之间的复杂相互作用.

结论:

  • 变量重要性分析提高了RF模型的解释性,用于预测老年人住院治疗.
  • 结果为临床应用提供了见解,包括医院需求预测和资源优化.
  • 未来的研究将探索对伴随性疾病的子组分析和先进的缺失数据技术.