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

Labeling Emotion

Labeling Emotion

Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...

You might also read

Related Articles

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

Sort by

Same author

"Anchoring-desolvating-shielding" spatially configurated Interface layer addressing the trade-off between Zn utilization, areal capacity and anti-calendar aging.

Journal of colloid and interface science·2026

Same author

USP24-dependent STAT2 stabilization mediates physiologic and pathologic bone formation.

Cell death & disease·2026

Same author

3DOM Perovskite Enabled Interfacial Microenvironment Regulation With Accelerated Complete Reconstruction to Grain-Boundary-Rich Nano-Copper for High-Current C<sub>2+</sub> Electrosynthesis.

Advanced materials (Deerfield Beach, Fla.)·2026

Same author

Simultaneous detection of SARS-CoV-2 proteins and nucleic acids by coupling PNIPAM with circle-to-circle amplification.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry·2026

Same author

STFusion: A Spatial-Temporal Dual-Pathway Network with Multi-scale Attention Fusion for Early Diagnosis of Parkinson's Disease.

Interdisciplinary sciences, computational life sciences·2026

Same author

The involvement of TNFRSF25 in age-related hearing loss.

Human genetics·2026

Search research articles

Related Experiment Video

Updated: May 7, 2026

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

Published on: April 1, 2016

Chinese EMR Named Entity Recognition Using Fused Label Relations Based on Machine Reading Comprehension Framework.

Junwen Duan, Shuyue Liu, Xincheng Liao

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|March 12, 2024

Summary

This study introduces a new model for Chinese electronic medical record (EMR) named entity recognition (NER). The Fusion Label Relations with MRC (FLR-MRC) model improves accuracy by considering relationships between entity types.

More Related Videos

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Related Experiment Videos

Last Updated: May 7, 2026

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese

Published on: April 1, 2016

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

Published on: June 29, 2021

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Area of Science:

Natural Language Processing
Medical Informatics
Artificial Intelligence

Background:

Chinese electronic medical records (EMR) pose unique challenges for Named Entity Recognition (NER) due to specialized language.
Traditional NER methods and current Machine Reading Comprehension (MRC) approaches have limitations in capturing inter-entity relationships.

Purpose of the Study:

To develop an enhanced MRC-based model for clinical NER that accounts for dependencies between entity types.
To improve the accuracy and robustness of NER in Chinese EMR data.

Main Methods:

Introduced the Fusion Label Relations with MRC (FLR-MRC) model.
Integrated graph attention networks to model interrelations between entity labels.
Applied the model to Chinese EMR datasets for NER task.

Main Results:

The FLR-MRC model achieved F1-scores of 0.6652 on the CMeEE dataset and 0.9101 on the CCKS2017-CNER dataset.
Demonstrated superior performance compared to existing clinical NER methods.
Effectively captured and utilized dependencies among entity types.

Conclusions:

The FLR-MRC model offers a significant advancement in clinical NER by incorporating label interrelations.
This approach enhances the capability of MRC frameworks for complex EMR data.
The model shows strong potential for improving information extraction from Chinese medical records.