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

Associative Learning

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...

Theory of Attribution II: Kelley's Covariation Theory

Theory of Attribution II: Kelley's Covariation Theory

Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus: Comparing...

Deductive Reasoning

Deductive Reasoning

Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction from inductive reasoning. It uses a general principle or law to predict specific results. From these general principles, a scientist can predict specific results that remain valid as long as the general principles are correct.For example, a researcher can make specific predictions from the hypothesis "butterflies are attracted...

Theory of Attribution I: Correspondent Inference Theory

Theory of Attribution I: Correspondent Inference Theory

Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...

Correlation and Causation

Correlation and Causation

Correlation and CausationStatistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. A relationship between variables shows correlation, but it does not show cause-and-effect. A direct cause-and-effect relationship requires additional controlled experiments. If no consistent relationship exists between the variables, then there is no correlation.Correlation versus CausationIf the dependent variable increases or decreases when the...

Attribution Theory

Attribution Theory

Behavior is a product of both the situation (e.g., cultural influences, social roles, and the presence of bystanders) and of the person (e.g., personality characteristics). Subfields of psychology tend to focus on one influence or behavior over others. Situationism is the view that our behavior and actions are determined by our immediate environment and surroundings. In contrast, dispositionism holds that our behavior is determined by internal factors (Heider, 1958). An internal factor is an...

You might also read

Related Articles

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

Sort by

Same author

Insights from multidisciplinary rare disease visits: Findings from wrap-up documents and participant surveys in a national diagnostic study.

Rare (Amsterdam, Netherlands)·2025

Same author

The Pursuit of Scientific Rigor and Definitional Clarity in Health Literacy Research.

Health literacy research and practice·2024

Same author

Research culture in biomedicine: what we learned, and what we would like to do about it.

Communications biology·2024

Same author

Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning.

Journal of the American Medical Informatics Association : JAMIA·2023

Same author

A practical strategy to use the ICD-11 for morbidity coding in the United States without a clinical modification.

Journal of the American Medical Informatics Association : JAMIA·2023

Same author

Participation in a national diagnostic research study: assessing the patient experience.

Orphanet journal of rare diseases·2023

Search research articles

Related Experiment Video

Updated: Jun 22, 2026

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

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

Published on: June 13, 2025

Auditing associative relations across two knowledge sources.

Lowell T Vizenor¹, Olivier Bodenreider, Alexa T McCray

¹Computer Task Group, Inc., Buffalo, NY, USA.

Journal of Biomedical Informatics

|May 29, 2009

Summary

This summary is machine-generated.

A new semantic method audits biomedical terminology relationships, finding 63% of associative relations in the Unified Medical Language System (UMLS) Metathesaurus are consistent with its Semantic Network. This highlights areas for improving biomedical data consistency.

Related Experiment Videos

Last Updated: Jun 22, 2026

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

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

Published on: June 13, 2025

Area of Science:

Biomedical Informatics
Medical Terminology
Knowledge Representation

Background:

Biomedical terminologies like the Unified Medical Language System (UMLS) contain complex associative relationships.
Ensuring the semantic consistency of these relationships is crucial for accurate data retrieval and analysis.
Existing methods for auditing these relationships may not fully capture semantic nuances.

Purpose of the Study:

To propose and evaluate a novel semantic method for auditing associative relationships within biomedical terminologies.
To assess the consistency of relationships in the UMLS Metathesaurus against its Semantic Network.
To identify opportunities for improving the semantic accuracy and mapping of biomedical knowledge sources.

Main Methods:

Utilized UMLS semantic groups to represent the domain and range of relationships.
Developed a mapping between Metathesaurus and Semantic Network relationships.
Compared the semantic signatures of Metathesaurus relationships to their mapped Semantic Network counterparts.
Analyzed the consistency of Metathesaurus relations based on this semantic comparison.

Main Results:

Of 177 associative relationships in the Metathesaurus, 84 (48%) showed high consistency with Semantic Network relationships.
Overall, 63% of approximately 1.8 million associative relations in the Metathesaurus were found to be consistent with the Semantic Network.
The auditing method provided insights into refining the mapping of associative relationships.

Conclusions:

Biomedical terminology developers should explicitly define the semantics of associative relationships.
The UMLS Semantic Network could be enhanced with new relationships and relations.
The proposed auditing method offers a valuable tool for the UMLS editing environment to improve relationship mapping.