Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Longitudinal Studies

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...

Longitudinal Research

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

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...

Study Designs in Epidemiology

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...

Introduction To Survival Analysis

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...

You might also read

Related Articles

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

Sort by

Same author

The ROBOKOP v1.0 knowledge graph system for exploring relationships between biomedical entities.

Scientific reports·2026

Same author

CellPheno: A High-throughput Computational Platform for Quantifying Cellular Resolution Whole Brain Microscopy Images.

bioRxiv : the preprint server for biology·2026

Same author

<i>Chd8</i> haploinsufficiency leads to molecular layer heterotopias and age-dependent cortical expansion.

bioRxiv : the preprint server for biology·2026

Same author

Contextualization or Rationalization? The Effect of Causal Priors on Data Visualization Interpretation.

IEEE transactions on visualization and computer graphics·2026

Same author

LinkML: an open data modeling framework.

GigaScience·2025

Same author

Think globally, barcode locally: nine years of macrofungi sampling reveals extensive biodiversity at the ordway-swisher biological station, a subtropical site in Florida.

Fungal biology·2025

Search research articles

Related Experiment Video

Updated: Oct 22, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

Enabling Longitudinal Exploratory Analysis of Clinical COVID Data.

David Borland, Irena Brain, Karamarie Fecho

|August 31, 2021

Summary

This study applied visual analytics to COVID-19 patient data, transforming clinical information for better disease understanding. Initial findings offer insights into patient trajectories and inform future research directions.

More Related Videos

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Related Experiment Videos

Last Updated: Oct 22, 2025

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Area of Science:

Medical Informatics
Data Visualization
Epidemiology

Background:

The COVID-19 pandemic necessitates advanced data analysis for disease comprehension.
Longitudinal clinical data offers valuable insights into patient health trajectories.
Visual analytics tools can aid in exploring complex health datasets.

Approach:

Applied existing event sequence visual analytics technologies.
Processed and transformed longitudinal clinical data from 998 COVID-19 patients.
Focused on data preparation for effective visual analysis.

Key Points:

Initial data transformation and processing steps were detailed.
Preliminary findings and observations from the visual analysis were presented.
Qualitative feedback highlighted system strengths and areas for improvement.

Conclusions:

The study represents initial steps in applying visual analytics to COVID-19 clinical data.
Lessons learned will guide future enhancements of visual analytics tools for pandemic research.
Further work is needed to refine the approach and address identified limitations.