Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Flow Sheet01:17

Flow Sheet

2.3K
Flowsheets are valuable tools in nursing documentation. They enable healthcare professionals to efficiently record and monitor various patient assessments and measurements in a consolidated format.
Here's a closer look at the examples of flowsheets commonly used by nurses:
Graphic Sheet Documentation:
2.3K
Flow Cytometry01:23

Flow Cytometry

14.7K
The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
14.7K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.0K
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...
1.0K
Nursing Clinical Information System01:27

Nursing Clinical Information System

976
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:
976

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Assessing the association of type 2 diabetes with skin health status: a study of the Northern Finland Birth Cohort 1966.

BMJ open·2026
Same author

Applicability of academic real-world data research in the case studies of the HTx project to practical health technology assessment work.

Frontiers in pharmacology·2026
Same author

Early-life immunological and microbial differences between East African and North European children.

Communications medicine·2026
Same author

Marine n-3 Long-Chain Polyunsaturated Fatty Acid Intake in Pregnancy and Risk of Early Life Infections in 3 Nordic Cohorts: A HEDIMED Consortium Study.

The Journal of nutrition·2026
Same author

Machine-Learning-Based Fatigue Trend Analysis on IMU Wearable Sensor Data from Construction Site Workers.

Sensors (Basel, Switzerland)·2025
Same author

Dietary intake of vitamins A, B, C, D and E and risk of islet autoimmunity and type 1 diabetes in genetically at-risk children: a prospective study from the DIPP birth cohort.

Diabetologia·2025

Related Experiment Video

Updated: Nov 4, 2025

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
06:01

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

Published on: December 12, 2019

8.7K

ClinFlow - An Interactive Application for Clinical Data Mining.

Oana Stoicescu1, Eija Ferreira1, Satu Tamminen1

  • 1Biomimetics and Intelligent Systems Group, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland.

Studies in Health Technology and Informatics
|May 27, 2021
PubMed
Summary

This study introduces a novel application simplifying clinical data analysis for researchers. The tool integrates medical expertise with data mining, enabling interactive data processing and visualization without programming knowledge.

Keywords:
RShinyanalysisclinicaldataminingtool

More Related Videos

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K
In Silico Clinical Trials for Cardiovascular Disease
09:09

In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

1.9K

Related Experiment Videos

Last Updated: Nov 4, 2025

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
06:01

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

Published on: December 12, 2019

8.7K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K
In Silico Clinical Trials for Cardiovascular Disease
09:09

In Silico Clinical Trials for Cardiovascular Disease

Published on: May 27, 2022

1.9K

Area of Science:

  • Clinical data analysis
  • Medical informatics
  • Data mining applications

Background:

  • Analyzing clinical data requires a blend of medical, statistical, and programming expertise.
  • Existing methods for clinical data mining can be inaccessible to researchers lacking specialized programming skills.

Purpose of the Study:

  • To bridge the gap between clinical expertise and computer science knowledge.
  • To provide an accessible application for clinical data analysis, eliminating the need for statistical programming.
  • To assist clinical researchers in data processing and visualization within an interactive environment.

Main Methods:

  • Development of a user-friendly application for clinical data analysis.
  • Interactive data processing and visualization capabilities.
  • Experimental evaluation using clinical data from Type 1 Diabetes studies.

Main Results:

  • The application was successfully evaluated on Type 1 Diabetes clinical data.
  • Results align with existing domain literature, validating the tool's utility.
  • Demonstrated value in exploratory data analysis and hypothesis testing for clinical studies.

Conclusions:

  • The developed application effectively supports clinical data analysis for researchers without programming expertise.
  • The tool facilitates interactive data exploration and hypothesis generation in clinical research.
  • This approach enhances the accessibility and efficiency of clinical data mining.