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

Dementia01:30

Dementia

503
Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....
503
Alzheimer's Disease: Treatment01:22

Alzheimer's Disease: Treatment

782
Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
782
Integrated Healthcare System01:20

Integrated Healthcare System

2.3K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
2.3K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.1K
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...
6.1K
Nursing Clinical Information System01:27

Nursing Clinical Information System

1.2K
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
1.2K
Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

1.6K
Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
1.6K

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

Cost utility and cost-effectiveness of the APPLE-Tree programme: Active Prevention in People at risk of dementia through Lifestyle, bEhaviour change and Technology to build REsiliEnce: economic evaluation embedded within a randomised controlled trial.

Age and ageing·2026
Same author

Deviations in effective connectivity explain different hallucination subtypes in Parkinson's disease psychosis.

Nature. Mental health·2026
Same author

Acceptability of Technologies to Support Early Dementia Detection: Qualitative Study With the Boston University Alzheimer's Disease Center Cohort.

Journal of medical Internet research·2026
Same author

Unbiased data-driven analysis of five amyloid-beta peptides for biomarker investigations in familial Alzheimer's disease.

Brain communications·2026
Same author

Brain-injury and Alzheimer's disease biomarkers are elevated in patients with suspected infection and physiological derangement: importance for context-specific interpretation of Alzheimer's biomarkers.

Brain communications·2026
Same author

The DREAMS START intervention for sleep in dementia: Long-term follow-up of a randomized controlled trial.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same journal

Predicting the risk of serious muscle disorders in individuals eligible for statin treatment in England: derivation and validation of a clinical prediction model.

The Lancet. Digital health·2026
Same journal

Ensuring the clinical impact of medical artificial intelligence.

The Lancet. Digital health·2026
Same journal

Precision medicine's inevitable trajectory toward rare-disease-sized cohorts: implications for machine learning and deep learning.

The Lancet. Digital health·2026
Same journal

Artificial intelligence-based retinal imaging for brain health assessment: a scoping review.

The Lancet. Digital health·2026
Same journal

Digital demands for chronic disease research and management.

The Lancet. Digital health·2026
Same journal

Large language models as experimental systems in human psychopathology: a modelling study.

The Lancet. Digital health·2026
查看所有相关文章

相关实验视频

Updated: Jan 11, 2026

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.8K

云计算为公平,数据驱动的痴呆症医学提供了云计算.

Marcella Montagnese1, Bojidar Rangelov2, Tom Doel3

  • 1Department of Psychology, University of Cambridge, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

The Lancet. Digital health
|November 9, 2025
PubMed
概括
此摘要是机器生成的。

开发用于痴呆症护理的人工智能受到数据问题的阻碍. 我们提出一种基于云的联合学习方法,以构建可适应的痴呆症预测模型,同时保护患者的隐私.

更多相关视频

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.9K
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.6K

相关实验视频

Last Updated: Jan 11, 2026

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.8K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.9K
Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
11:21

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

8.6K

科学领域:

  • 神经学 神经学
  • 人工智能的人工智能
  • 医疗信息学 医疗信息学

背景情况:

  • 痴呆症是一个日益增长的全球健康挑战,需要先进的预测模型来开发新药和临床应用.
  • 机器学习 (ML) 在痴呆症研究中显示出潜力,但在常规医疗保健中面临重大障碍,主要是由于数据不可用,并导致数据漂移.
  • 医疗保健中现有的ML应用程序未得到充分利用,特别是基于图像的决策支持,这阻碍了公平的现实世界翻译.

研究的目的:

  • 为痴呆症研究提供可扩展的基于云的基础设施作为代码解决方案.
  • 解决数据不可用性和数据漂移挑战,开发用于痴呆症护理的人工智能模型.
  • 为了实现创建强大的和可适应的人工智能 (AI) 模型的痴呆症医学,同时保持患者的隐私.

主要方法:

  • 实现基于云的基础设施作为代码 (IaC) 解决方案.
  • 整合保护隐私的联合学习 (FL) 技术.
  • 试点架构以证明其在医疗保健环境中的可扩展性和有效性.

主要成果:

  • 展示了一个可扩展的,基于云的基础设施,用于在痴呆症研究中开发AI模型.
  • 成功实施保护隐私的联合学习,保持患者数据的本地化和安全性.
  • 实现了可适应人工智能模型的开发,克服了数据漂移障碍.

结论:

  • 基于云的联合学习为在痴呆症医学中开发AI提供了可行的解决方案.
  • 这种方法提高了数据安全性和患者隐私,这对于医疗保健应用至关重要.
  • 拟议的基础设施和代码库可以加速研究和人工智能在痴呆症护理中的现实世界翻译.