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

Statistical Analysis: Overview01:11

Statistical Analysis: Overview

7.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
7.7K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

810
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...
810
Biostatistics: Overview01:20

Biostatistics: Overview

381
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
381
Multiple Bar Graph01:07

Multiple Bar Graph

8.1K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
8.1K
Scatter Plot01:15

Scatter Plot

9.8K
The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
9.8K
Organization of Genes02:07

Organization of Genes

69.9K
Overview
69.9K

You might also read

Related Articles

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

Sort by
Same author

Multiscale heterogeneity of atypical functional connectivity in autism.

Nature. Mental health·2026
Same author

Prenatal Alcohol Exposure Predicts Academic Outcomes from Childhood to Adolescence: A Prospective Longitudinal Study Based on Meconium Ethyl Glucuronide.

Behavioral sciences (Basel, Switzerland)·2026
Same author

Adaptive stepped care in preschool-age children with ADHD symptoms: a multicentre study including two consecutive randomised controlled trials (ESCApreschool).

European child & adolescent psychiatry·2026
Same author

Model-based analysis of stop-signal data reveals robust neural and clinical correlates of evidence accumulation but not inhibition.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2026
Same author

Bullying victimization and brain development: a longitudinal structural magnetic resonance imaging study from adolescence to early adulthood.

Translational psychiatry·2026
Same author

A longitudinal DNA methylation atlas and its link to brain structure and mental health.

Molecular psychiatry·2026
Same journal

Predictors of Conversion from Major Depressive Disorder to Bipolar Disorder: A Population-Based PADRIS-PRESTO Cohort Study in Catalonia.

European psychiatry : the journal of the Association of European Psychiatrists·2026
Same journal

Precision medicine in mental health: applications, challenges, and recommendations - CORRIGENDUM.

European psychiatry : the journal of the Association of European Psychiatrists·2026
Same journal

Real-world effectiveness and safety of intranasal esketamine for treatment-resistant depression: data from the enTRD registry.

European psychiatry : the journal of the Association of European Psychiatrists·2026
Same journal

Trajectory of response to esketamine nasal spray for treatment resistant depression: findings from ESCAPE-TRD.

European psychiatry : the journal of the Association of European Psychiatrists·2026
Same journal

Identification of distinct clinical phenotypes and their neurobiological signatures in stress-exposed individuals: A multimodal machine learning approach.

European psychiatry : the journal of the Association of European Psychiatrists·2026
Same journal

The interplay among narcissistic vulnerability, interpersonal sensitivity, and metacognitive integration: A network analysis approach.

European psychiatry : the journal of the Association of European Psychiatrists·2026
See all related articles

Related Experiment Video

Updated: Sep 20, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

693

ItemComplex: A Python-based visualization framework for ex-post organization and integration of large language-based

Karina Janson1,2, Karl Gottfried1, Olaf Reis3

  • 1Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.

European Psychiatry : the Journal of the Association of European Psychiatrists
|May 26, 2025
PubMed
Summary
This summary is machine-generated.

ItemComplex is a Python framework for visualizing large mental health datasets. It helps researchers and clinicians navigate complex data, identify new insights, and organize information for analysis.

Keywords:
big dataconstructscontent networksdata navigationdata structuringdata visualizationitems

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

11.5K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.3K

Related Experiment Videos

Last Updated: Sep 20, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

693
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

11.5K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.3K

Area of Science:

  • Data Science
  • Computational Psychiatry
  • Bioinformatics

Background:

  • Increasingly large datasets in mental health research pose challenges for visualization and analysis.
  • Existing tools lack multi-level integration for organizing and analyzing diverse data sources.
  • Need for sophisticated visualization tools for questionnaire, digital, and clinical data.

Purpose of the Study:

  • Introduce ItemComplex, a Python framework for ex-post visualization of large datasets.
  • Enable effective data organization and construction for subsequent analyses.
  • Facilitate the identification of new content networks and graphs.

Main Methods:

  • ItemComplex is a Python-based framework for ex-post visualization.
  • It recognizes instrument alignments and identifies content networks based on item similarities.
  • Analysis leverages shared and differential conceptual bases within and across datasets.

Main Results:

  • ItemComplex successfully visualized large datasets from four cohort studies.
  • The framework enables reliable, informative, and quick navigation of big data.
  • Facilitates extraction of new insights into construct representations and concept identification.

Conclusions:

  • ItemComplex is an efficient tool for big data management and analysis in mental health.
  • Addresses the complexity of modern datasets to unlock hidden potential.
  • Adjustable for individual datasets and user preferences in research and clinical settings.