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

Assessment of the Mouth

Assessment of the Mouth

A thorough mouth assessment, including inspection and palpation of the lips, gums, tongue, tonsils, uvula, and pharynx, is crucial in detecting potential health issues. Diseases ranging from oral cancer to systemic conditions like diabetes could be identified early through careful oral examination. This article provides a detailed guide on conducting a comprehensive mouth assessment.
Mouth Inspection
The inspection begins with visually examining the mouth for symmetry, color, and size.

The Tongue and Taste Buds

The Tongue and Taste Buds

The surface of the tongue is covered with various small bumps called papillae, which either distribute what has been ingested (filiform papillae) or contain the sensory taste (or gustatory) receptor cells (fungiform, circumvallate, and foliate papillae). Embedded within each taste-related papilla are the taste buds—clusters of 30 to 100 gustatory receptor cells.

Observational Learning

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...

Tongue

Tongue

The human tongue is a fascinating and complex organ, responsible for various essential functions such as swallowing, speech, and taste. It is also subject to various conditions and diseases. In this article, we delve into the anatomy of the tongue, its roles, and some common conditions that can affect it.
Anatomical Position in the Oral Cavity
The tongue is located within the oral cavity, also known as the mouth. It is attached to the floor of the mouth by a fold of mucous membrane called the...

You might also read

Related Articles

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

Sort by

Same author

Systemic predictors in middle ear cholesterol granuloma: methodological and translational considerations.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery·2026

Same author

Phillyrin protects against myocardial ischemia/reperfusion injury by promoting KNL1 K605 acetylation to inhibit the p53/p21 pathway.

Acta biochimica et biophysica Sinica·2026

Same author

Application of Multistrategy Improvement Gray Wolf Algorithm to Optimize Extreme Gradient Boosting in Emergency Triage.

Journal of emergency nursing·2026

Same author

ZER1 Restrains Pressure Overload-Induced Cardiac Remodeling by Targeting DVL2 for Gly/N-Degron-Dependent Degradation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

Cardiac xenotransplantation: Progress, barriers, and pathways toward clinical translation.

Journal of biomedical research·2026

Same author

Calibration, generalization, and explainability: AI challenges behind bedside EEG prognostication.

Resuscitation·2026

Search research articles

Related Experiment Video

Updated: Sep 18, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

Weakly supervised multiple-instance active learning for tooth-marked tongue recognition.

Feilin Deng¹, Shangxuan Li¹, Zizhu Yang¹

¹School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China.

Frontiers in Physiology

|June 26, 2025

Summary

This summary is machine-generated.

This study introduces a new weakly supervised active learning model for recognizing tooth-marked tongues in Traditional Chinese Medicine. The method significantly reduces annotation workload and costs while maintaining high diagnostic accuracy.

Keywords:

active learning multiple instance learning pseudo label tooth-marked tongue weakly supervised learning

More Related Videos

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

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Published on: January 3, 2017

Related Experiment Videos

Last Updated: Sep 18, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

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

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Published on: January 3, 2017

Area of Science:

Medical Diagnostics
Artificial Intelligence
Traditional Chinese Medicine

Background:

Recognizing tooth-marked tongues is crucial in Traditional Chinese Medicine (TCM) diagnostics.
Current deep learning methods for tooth mark detection are labor-intensive due to extensive manual labeling and tongue segmentation requirements.
There is a need for efficient methods to reduce annotation workload while maintaining diagnostic accuracy for tooth-marked tongue recognition.

Purpose of the Study:

To propose a weakly supervised multiple-instance active learning model for tooth-marked tongue recognition.
To eliminate the need for preprocessing tongue segmentation.
To reduce the annotation workload and cost for TCM tooth mark recognition.

Main Methods:

A one-stage method was developed to generate tooth mark instances without pre-segmentation.
A semi-supervised learning paradigm was employed to pseudo-label unlabeled tongue images, enhancing active learning efficiency.
An instance-level hybrid query method was introduced to account for the diversity of tooth marks.

Main Results:

The proposed method achieved an accuracy of 93.88% in tooth-marked tongue recognition on clinical data.
The method's performance is comparable to traditional annotation methods (image-level, instance-level, pixel-level) that require extensive labeling.
The approach outperformed recently introduced weakly supervised methods.

Conclusions:

The proposed weakly supervised active learning model is effective for tooth-marked tongue recognition with minimal image-level annotation.
The method significantly reduces annotation costs compared to methods requiring extensive tooth marker data.
This approach offers a practical solution for improving diagnostic efficiency in TCM by leveraging limited annotations.