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Related Concept Videos

How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
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How Data are Classified: Numerical Data00:59

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
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Data Reporting and Recording01:24

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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Data Validation01:15

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Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
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Data Validation01:03

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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.
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Data Collection II01:29

Data Collection II

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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...
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How Omics Data Can Be Used in Nephrology.

Eugene P Rhee1

  • 1Nephrology and Endocrinology Divisions, Massachusetts General Hospital, Boston, MA.

American Journal of Kidney Diseases : the Official Journal of the National Kidney Foundation
|February 27, 2018
PubMed
Summary
This summary is machine-generated.

Omics technologies analyze biological data like genomes to advance nephrology. These tools offer new ways to understand kidney disease, improving patient diagnosis and treatment.

Keywords:
Omicsanalytic methodsgenomicsmetabolomicsnephrology researchproteomicsrevsystems biologytranscriptomicstranslational researchurinomics

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Area of Science:

  • Genomics
  • Proteomics
  • Metabolomics
  • Transcriptomics
  • Nephrology

Background:

  • High-throughput omics technologies analyze multiple biological data domains (genome, transcriptome, proteome, metabolome).
  • These approaches have driven significant discoveries in medicine, including nephrology.
  • Omics data presents challenges for clinical synthesis, necessitating a bridge to clinical practice.

Purpose of the Study:

  • To provide nephrologists with an overview of omics technologies.
  • To frame omics tools as extensions of current clinical patient care approaches.
  • To highlight the clinical relevance of omics in nephrology.

Main Methods:

  • Review of omics technologies and their applications in nephrology.
  • Discussion of how omics data can be integrated into clinical decision-making.
  • Explanation of the conceptual framework underlying omics approaches.

Main Results:

  • Omics technologies reinforce the role of genetic mutations in kidney disorders.
  • They expand the known catalog of uremic molecules in kidney failure.
  • Omics enhance urine analysis beyond traditional urinalysis and kidney biopsy characterization.

Conclusions:

  • Omics technologies offer unbiased molecular discovery.
  • These tools facilitate a more mechanistic and individualized approach to diagnosing and treating kidney diseases.
  • Application of omics in nephrology promises to refine patient care strategies.