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相关概念视频

Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Data Collection II01:29

Data Collection II

The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and family,...
Data Collection III01:05

Data Collection III

The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the patient.
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...

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相关实验视频

Updated: Jul 6, 2026

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
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扩展了伦巴第新生儿查数据集.

G Lopiano1, L Alberti2, C Cereda2

  • 1University of Milano Bicocca, Computer Science, Milano, 20125, Italy. g.lopiano1@campus.unimib.it.

Scientific data
|December 10, 2025
PubMed
概括

新生儿查 (NS) 数据现在是公开的,为研究遗传疾病和早期诊断干预提供了宝贵的资源. 这一数据集支持新生儿健康和数据驱动的医疗分析的进展.

科学领域:

  • 医学研究 医学研究
  • 公共卫生 公共卫生
  • 遗传学 遗传学是一种遗传学.

背景情况:

  • 新生儿查 (NS) 是20世纪60年代建立的一个关键的二次预防计划.
  • NS可以检测新生儿的罕见遗传疾病,使早期干预能够预防严重的健康问题.
  • 对于NS研究的公开可访问的数据集存在重大差距.

研究的目的:

  • 提供新生儿查 (NS) 血样和相关数据的综合数据集.
  • 为医学研究遗传性疾病,早期诊断和治疗疗效提供宝贵的见解.
  • 支持数据驱动的医疗分析和政策制定方面的学术研究.

主要方法:

  • 汇编了伦巴第的一个十年的NS数据.
  • 包括血液样本和相关患者信息.
  • 综合数据集的公开发布.

主要成果:

  • 现在可以获得近十年来伦巴第地区NS的综合数据集.
  • 数据集包含血液样本和相关信息.
  • 这些数据可用于医学和学术研究.

结论:

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  • 这个NS数据集的公开可用性增强了新生儿健康的研究机会.
  • 该资源可以有助于改进对遗传疾病的早期干预策略.
  • 促进数据驱动的医疗分析和新生儿护理政策制定.