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Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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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

How Data are Classified: Numerical Data

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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.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
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Data Reporting and Recording01:24

Data Reporting and Recording

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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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Nursing Clinical Information System01:27

Nursing Clinical Information System

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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:
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Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Updated: Feb 14, 2026

An Automated Radiosynthesis of [68Ga]Ga-FAPI-46 for Routine Clinical Use
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[Big data from clinical routine].

U Mansmann1

  • 1Institut für Medizinische Informatik, Biometrie und Epidemiologie, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland. ulrich.mansmann@lmu.de.

Zeitschrift Fur Rheumatologie
|February 18, 2018
PubMed
Summary
This summary is machine-generated.

Data-driven medicine is transforming healthcare by leveraging big data for personalized patient care. Integrating health data into IT infrastructures can create a learning healthcare system for improved medical evidence generation.

Keywords:
Data collectionEvidence-based medicineInformation processingMedical informaticsPatient data privacy

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Area of Science:

  • Medical Informatics
  • Digital Health
  • Evidence-Based Medicine

Background:

  • Evolution of evidence-based medicine from natural sciences to clinical epidemiology.
  • Emergence of big data as a driving force in healthcare.
  • Focus on comprehensive health data tracking for individuals and populations.

Purpose of the Study:

  • Discuss implications of data-driven medicine.
  • Examine integration of data-driven medicine into clinical care.

Main Methods:

  • Presentation of EU-wide discussions on data-driven medicine development.

Main Results:

  • Identified needs: harmonized data formats, advanced data processing and analysis, secure data exchange, robust legal frameworks, and ethical considerations.
  • Emphasized need for pilot projects for open discussion on data-driven medicine's benefits and challenges.
  • Highlighted BMBF Arthromark project and Medical Informatics Initiative as key examples.

Conclusions:

  • Digital revolution is reshaping clinical practice with unprecedented data generation and storage capabilities.
  • Potential to develop a learning healthcare system by integrating medical evidence principles with IT infrastructure.
  • Data-driven approaches are crucial for advancing medical knowledge and patient outcomes.