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相关概念视频

Primary Healthcare Services01:30

Primary Healthcare Services

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Primary care promotes wellness and prevents disease. This care includes health promotion, education, protection (such as immunizations), early disease screening, and environmental considerations. Settings providing this type of healthcare include physician offices, public health clinics, school nursing, and community health nursing.
In 1978, international leaders convened in Alma-Ata, Kazakhstan, for what would be a pivotal event in global health. The Alma-Ata Declaration was the first to call...
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Levels of Health Promotion and Illness Prevention01:26

Levels of Health Promotion and Illness Prevention

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Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
In primary prevention, actions taken before disease onset prevent the disease from...
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Preventive Healthcare Services01:30

Preventive Healthcare Services

1.8K
Preventive healthcare services keep people healthy via frequent check-ups, screening, and counseling. They primarily aid in disease prevention rather than treating an acute or chronic illness. Preventive treatment also keeps individuals productive and energetic, allowing them to work well into their retirement years. Examples of preventive care services include:
1.8K
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
439
Healthcare Agencies II01:17

Healthcare Agencies II

1000
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,...
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Methods Of Healthcare Delivery System01:26

Methods Of Healthcare Delivery System

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At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
The managed care system is designed to control the cost while maintaining the quality of care. The patient's care from admission to discharge is planned by the primary care provider or the case manager, also known as the gatekeeper. In a managed care system, the number of care providers is...
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Determining Soil-transmitted Helminth Infection Status and Physical Fitness of School-aged Children
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公共卫生 公共卫生

Jennifer Rohrs1, Tom Paterson1, Don Breuner1

  • 1Fulcrum Neuroscience, Palo Alto, CA, USA.

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概括
此摘要是机器生成的。

我们开发了一个因果模型来整合各种阿尔茨海默病和相关痴呆症 (ADRD) 数据,从而实现个性化风险预测. 这种方法协调了相互矛盾的发现,并指导了针对ADRD的定制预防策略.

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科学领域:

  • 计算神经科学是一种计算神经科学.
  • 生物医学工程 生物医学工程
  • 医学中的人工智能.

背景情况:

  • 关于阿尔茨海默病和相关痴呆症 (ADRD) 风险因素 (遗传,生活方式,环境) 的大量数据缺乏对个体风险预测的共识.
  • 对运动,糖尿病和维生素D等因素的相互矛盾的研究结果使ADRD风险评估复杂化.
  • 目前的方法难以整合多样化的数据,阻碍了个性化的预测和ADRD的预防.

研究的目的:

  • 开发一种因果模型来整合不同的ADRD风险和弹性数据.
  • 调和各种关于ADRD风险因素的研究中的相互矛盾的发现.
  • 通过使用数字双胞胎,实现个性化的ADRD风险预测和个性化的治疗策略.

主要方法:

  • 使用工程原理 (质量平衡,反循环) 开发了大脑健康和神经退行的一种机械模型.
  • 用各种数据 (体外,体内,临床,死后) 校准模型,并确定了生物相关的变异性.
  • 创建了一个数字人口复制危险比率和卡普兰-梅尔数据作为贝叶斯先验.

主要成果:

  • 因果模型协调相互矛盾的数据,提供一个一致的框架来比较风险因素效应大小.
  • 基于失败的生物补偿机制,分层数字群体分为子组.
  • 使用贝叶斯推理创建个人数字双胞胎,以进行个性化的ADRD风险预测和治疗指导.

结论:

  • 计算工具对于将ADRD研究综合到因果假设和建模疾病病因学中至关重要.
  • 与人工智能集成的机械模型为结合各种数据集和先前知识提供了一个理想的框架.
  • 创建数字双胞胎的可扩展平台可以改善医疗保健,并优化ADRD个性化治疗策略.