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

Peptic Ulcer Disease V: Surgical Management and Nursing Care01:25

Peptic Ulcer Disease V: Surgical Management and Nursing Care

228
Surgical management and nursing care are crucial in treating Peptic Ulcer Disease (PUD). Here is an organized and enhanced overview of the surgical interventions and the associated nursing care for PUD:
Surgical Interventions for Peptic Ulcer Disease
228
Current Trends in Nursing I01:28

Current Trends in Nursing I

1.4K
Current trends in nursing include:
1.4K
Current Trends in Nursing II01:30

Current Trends in Nursing II

1.2K
Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
1.2K
Appendicitis-II: Diagnostic Studies and Management01:29

Appendicitis-II: Diagnostic Studies and Management

64
Diagnosing and managing appendicitis requires a structured and comprehensive approach that spans from initial assessment to postoperative care. Here is an overview of the process:
Diagnosing Appendicitis
It requires a multifaceted approach, starting with a detailed physical examination to pinpoint the location and nature of the pain and identify any associated symptoms. Laboratory tests play a crucial role. A complete Blood Count (CBC) typically reveals leukocytosis (an increased number of...
64
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.2K
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.2K

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

Electro-Acupuncture Ameliorated MPTP-Induced Parkinsonism in Mice via TrkB Neurotrophic Signaling.

Frontiers in neuroscience·2019
Same author

Enzyme characterization and biological activities of a resuscitation promoting factor from an oil degrading bacterium <i>Rhodococcus erythropolis</i> KB1.

PeerJ·2019
Same author

MXene Boosted CoNi-ZIF-67 as Highly Efficient Electrocatalysts for Oxygen Evolution.

Nanomaterials (Basel, Switzerland)·2019
Same author

A Biomimetic Hierarchical Nanointerface Orchestrates Macrophage Polarization and Mesenchymal Stem Cell Recruitment To Promote Endogenous Bone Regeneration.

ACS nano·2019
Same author

Adjacent intact nociceptive neurons drive the acute outburst of pain following peripheral axotomy.

Scientific reports·2019
Same author

Daily intake of soft drinks is associated with symptoms of anxiety and depression in Chinese adolescents.

Public health nutrition·2019
Same journal

Effectiveness of a scenario-based gamified virtual reality training on nurses' basic life support knowledge: a randomized controlled trial.

BMC nursing·2026
Same journal

Adaptation of the state self-compassion scale short form into Turkish: a methodological study.

BMC nursing·2026
Same journal

Latent profiles of nurses' attitudes toward artificial intelligence in nursing and associated factors: a cross-sectional study.

BMC nursing·2026
Same journal

Moral distress and job satisfaction among oncology and hematology nurses in Saudi Arabia.

BMC nursing·2026
Same journal

The relationships among academic self-efficacy, educational stress, and academic motivation in nursing students: a structural equation modeling analysis.

BMC nursing·2026
Same journal

Evidence-based nursing practice for the removal of peripheral arterial catheters in adult patients.

BMC nursing·2026
查看所有相关文章

相关实验视频

Updated: Jun 4, 2025

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

基于机器学习预测消化病房的护理工作量:一项前性研究

Yulei Song1, Xueqing Zhang1, Dan Luo1

  • 1School of Nursing, Nanjing University of Chinese Medicine, Nanjing, 210023, China.

BMC nursing
|December 19, 2024
PubMed
概括
此摘要是机器生成的。

机器学习通过分析患者因素,准确地预测动态护理工作量. 这种动态预测模型增强了护理管理和资源配置,以提高患者安全.

关键词:
机器学习是机器学习.护理工作负载的护理工作量.预测 预测 预测

更多相关视频

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
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.7K

相关实验视频

Last Updated: Jun 4, 2025

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
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.7K

科学领域:

  • 护理 护理 护理
  • 医疗信息学 医疗信息学
  • 机器学习 机器学习

背景情况:

  • 护理工作量对于人员分配和患者安全至关重要.
  • 截面研究限制了准确的工作负载预测.
  • 静态模型无法考虑纵向变化,影响管理决策.

研究的目的:

  • 为动态护理工作负载预测开发机器学习模型.
  • 利用患者的特征来预测护理时间需求.

主要方法:

  • 在中国两家普通医院进行前性队列研究 (2019年3月-2021年8月).
  • 在1339个医院日内收集了133名患者的数据,包括患者特征和直接护理时间.
  • 应用多重线性回归和机器学习 (随机森林) 用于纵向工作负载分析和预测.

主要成果:

  • 平均直接护理工作量在住院期间差异很大.
  • 影响工作负载的关键因素包括并发症,并发症,BMI,收入,过去的疾病,SCS和ADL.
  • 随机森林模型实现了高预测性能 (R2: 0.74).

结论:

  • 患者的自我护理能力,并发症和并发症是护理工作量变化的主要驱动因素.
  • 机器学习,特别是随机森林算法,有效地利用各种患者数据预测护理工作量.
  • 开发的定量模型有助于护理经理在主动工作负载管理和资源规划.