Jove
Visualize
联系我们

相关概念视频

Ethical Standards II01:23

Ethical Standards II

795
Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
Nurses are entrusted with upholding various ethical principles and standards. Nurses forge solid therapeutic relationships using trust, empathy, autonomy, confidentiality, and professional competence.
Confidentiality is crucial, embodying respect for individual privacy...
795
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.8K
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...
5.8K
Ethical Standards I01:25

Ethical Standards I

962
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
962
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

188
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:
188
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

628
The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
628
Healthcare Agencies II01:17

Healthcare Agencies II

749
There are various healthcare agencies in the United States—some of which are managed by religious institutions and others by different government branches.
Parish nursing is a growing specialty nursing profession that focuses on holistic healthcare, health promotion, and illness prevention. It blends professional nursing practice with a health ministry, focusing on health and healing within the context of a Christian community. Parish nurses serve as health educators, referral sources,...
749

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

Mantle cell lymphoma artificial intelligence prognostic index using hematoxylin and eosin histology.

Leukemia·2026
Same author

Association of IgG N-Glycans With Adverse Outcomes in CKD.

Kidney international reports·2026
Same author

The blood metabolome of brain health in midlife and influences of genes, microbiome and exposome.

Nature aging·2026
Same author

A lipidomic based metabolic age score for monitoring the effects of lifestyle and diet on metabolic disease risk.

Research square·2026
Same author

Circulating lipids are related to longitudinal changes of ATN biomarkers for Alzheimer's disease.

Molecular psychiatry·2026
Same author

Educational inequalities are associated with distinct metabolomic and gut microbiome patterns in adults.

Social science & medicine (1982)·2026
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

相关实验视频

Updated: Sep 9, 2025

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

7.2K

客户端机器学习模型用于保护隐私的医疗预测 - 部署案例研究

Yacoub Abelard Njipouombe Nsangou1,2, Rajib Kumar Halder3, Ashraf Uddin4

  • 1Dept. of Medical Bioinformatics, University Medical Center Göttingen, Germany.

Studies in health technology and informatics
|September 3, 2025
PubMed
概括

这项研究通过直接在Web浏览器中运行医疗保健机器学习 (ML) 和深度学习 (DL) 模型的隐私保护方法. 这种客户端执行确保敏感的患者数据在用户的设备上保持安全.

关键词:
临床情况机密性决策支持系统深度学习机器学习隐私问题网络浏览器

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
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

2.2K

相关实验视频

Last Updated: Sep 9, 2025

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

7.2K
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
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

2.2K

科学领域:

  • 计算科学
  • 医疗信息学
  • 机器学习

背景情况:

  • 医疗保健中的传统以服务器为中心的机器学习 (ML) 和深度学习 (DL) 模型涉及向外部服务器传输敏感的患者数据,造成重大隐私风险.
  • 像Flask这样的现有框架便于服务器端的处理,强调了需要更安全的替代方案.

研究的目的:

  • 展示完全在Web浏览器中执行医疗预测模型的隐私保护方法.
  • 消除与传统医疗保健ML/DL应用中的数据传输相关的隐私问题.

主要方法:

  • 利用基于浏览器的ML/DL技术,包括TensorFlow.js和ONNX运行时Web.
  • 基于模型复杂性的三种策略:简单模型的直接JavaScript,中等复杂模型的ONNX运行时Web (例如随机森林) 和复杂深度学习模型的TensorFlow.js (例如优化卷积神经网络).
  • 确保所有计算都在用户设备上执行.

主要成果:

  • 在客户端部署医疗预测模型是可行的和有效的.
  • 在客户端执行时保留模型的原始性能指标.
  • 通过将患者数据局部化来实现大量的隐私利益.

结论:

  • 用户的设备上保证保留患者数据,从而减轻数据传输的风险.
  • 这种方法对于优先考虑数据保密的医疗机构尤其有利.
  • 客户端执行模型还支持医疗保健应用程序的离线功能.