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

Overview of Biostatistics in Health Sciences01:19

Overview of Biostatistics in Health Sciences

3.6K
Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
3.6K
Biostatistics: Overview01:20

Biostatistics: Overview

449
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...
449
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
Data: Types and Distribution01:19

Data: Types and Distribution

982
In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...
982
Genomics02:02

Genomics

38.4K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
38.4K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.9K

You might also read

Related Articles

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

Sort by
Same author

Medication-related suicide plans in children and adolescents: findings from crisis conversations.

Injury epidemiology·2026
Same author

Dynamic thermodynamic-informational entropic relationship (TIER) models of selective vulnerability to neurodegeneration.

bioRxiv : the preprint server for biology·2026
Same author

Interpretable machine learning uncovers structural determinants of Wnt-Wntless binding specificity from atomistic simulations.

Communications chemistry·2026
Same author

Desiderata for a biomedical knowledge network: opportunities, challenges and future directions.

Bioinformatics advances·2026
Same author

Governing real-world health data as a public utility.

Science (New York, N.Y.)·2026
Same author

Planned Suicide Methods in Crisis Conversations: Effects of Age and Gender.

JAACAP open·2025
Same journal

Social Drivers of Health in the Electronic Health Record.

Annual review of biomedical data science·2026
Same journal

Artificial Intelligence in Image-Based Cardiovascular Disease Analysis.

Annual review of biomedical data science·2026
Same journal

Reclaiming Data, Restoring Health: The Indigenous Biomedical Data Science Renaissance.

Annual review of biomedical data science·2026
Same journal

Modeling the Language of Codons with Artificial Intelligence.

Annual review of biomedical data science·2026
Same journal

Exploring Genetic Variations Associated with the Immune Response in Underrepresented Populations.

Annual review of biomedical data science·2026
Same journal

Sex and the Genome: Divergent Genetic Architecture Across the Human Lifespan.

Annual review of biomedical data science·2026
See all related articles

Related Experiment Video

Updated: Nov 6, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.9K

Knowledge-Based Biomedical Data Science.

Tiffany J Callahan1, Ignacio J Tripodi2, Harrison Pielke-Lombardo1

  • 1Computational Bioscience Program and Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado 80045, USA.

Annual Review of Biomedical Data Science
|May 6, 2021
PubMed
Summary
This summary is machine-generated.

Biomedical data science uses knowledge graphs to integrate complex biological and clinical data. This review highlights advancements in creating and applying these knowledge systems for data analysis.

Keywords:
Semantic Webknowledge discoveryknowledge graphknowledge graph embeddingsnatural language processingontology

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

842
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.9K

Related Experiment Videos

Last Updated: Nov 6, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.9K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

842
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.9K

Area of Science:

  • Biomedical data science
  • Artificial Intelligence in Medicine
  • Knowledge Representation

Background:

  • Biomedical data science leverages formally represented knowledge, often via knowledge graphs, for computational systems.
  • Existing systems face challenges in integrating and analyzing diverse clinical and biological data.

Purpose of the Study:

  • To survey recent advancements in knowledge-based systems for biomedical data science.
  • To review progress in constructing and applying knowledge graphs in clinical and biological research.

Main Methods:

  • Review of literature on knowledge graph construction and application in biomedicine.
  • Analysis of the interplay between knowledge graphs and machine learning.
  • Examination of natural language processing techniques for knowledge graph creation.

Main Results:

  • Significant progress in developing knowledge-based approaches for clinical and biological data science.
  • Advancements in methods for creating and expanding biomedical knowledge graphs.
  • Integration of knowledge graphs with machine learning shows promise.

Conclusions:

  • Knowledge-based approaches are crucial for addressing complex biomedical data science challenges.
  • Continued development in knowledge graph construction and integration with machine learning will advance biomedical research.