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相关概念视频

Genetic Screens02:46

Genetic Screens

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
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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...
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Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
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Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

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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...
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Data Validation01:03

Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
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Kaplan-Meier Approach01:24

Kaplan-Meier Approach

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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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相关实验视频

Updated: Jan 8, 2026

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

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在选计划中管理数据:挑战和解决方案

Hugo Monteiro1, Mariana Oliveira1, Ricardo Martinho2

  • 1Faculdade de Medicina. Universidade do Porto. Porto. Portugal.

Acta medica portuguesa
|December 16, 2025
PubMed
概括
此摘要是机器生成的。

大数据分析可以通过改进数据管理,从存档到实时处理和预测建模来简化人口健康查计划. 这一框架提高了公共卫生倡议的效率,资源优化和患者护理.

关键词:
大数据的大数据大数据数据管理数据管理诊断查计划 诊断查计划公共卫生 公共卫生

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相关实验视频

Last Updated: Jan 8, 2026

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

Published on: January 11, 2020

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科学领域:

  • 公共卫生信息学 公共卫生信息学
  • 健康 数据科学 数据科学
  • 医疗保健管理的管理

背景情况:

  • 基于人口的查计划对于早期发现疾病和降低成本至关重要.
  • 扩展程序产生大量的数据,需要结构化的数字解决方案.
  • 有效的数据管理对于优化查工作流程和患者结果至关重要.

研究的目的:

  • 为医疗保健查中的大数据分析提供一个务实的框架.
  • 引导医疗保健专业人员和管理人员将数据分析集成到常规工作流程中.
  • 用现实世界的例子来说明大数据概念的应用.

主要方法:

  • 系统存档使用基于云的存储来进行安全的数据维护.
  • 实时处理用于快速决策和患者管理.
  • 数据转换和集成到集中式分析平台.
  • 先进的分析,包括过程挖掘和预测建模.
  • 实时可视化工具用于运营洞察力.

主要成果:

  • 结构化数据管理显著提高了运营效率和医疗保健的可访问性.
  • 灵活的数字基础设施对于适应公共卫生危机至关重要.
  • 大数据分析可以揭示效率低下,并优化选计划中的资源配置.
  • 预测模型有助于早期识别有风险的个体.

结论:

  • 采用大数据分析需要对数字基础设施,专业培训和数据治理进行投资.
  • 对数据管理的结构化方法提高了预防性医疗保健计划的有效性.
  • 通过数据驱动的洞察力,可以实现选工作流程的持续改进.