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Related Concept Videos

Oral Cavity01:11

Oral Cavity

3.0K
The oral cavity, or the mouth, is a complex structure in humans that plays a vital role in our day-to-day lives. Its role is not only in chewing and swallowing food; it also plays a role in speech and facial expressions.
Teeth: The teeth are the hardest structures in our bodies. Humans have two sets of teeth throughout their lifetime: deciduous (baby) teeth and permanent teeth. Each tooth consists of several parts: the crown (visible part), the root (embedded in the jaw), enamel (hard outer...
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Oral Hypoglycemic Agents: Glinides01:06

Oral Hypoglycemic Agents: Glinides

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Repaglinide (Prandin) and Nateglinide (Starlix), known as glinides, are oral insulin secretagogues that stimulate insulin release from pancreatic β cells by closing the ATP-sensitive potassium channels (KATP channel). Repaglinide controls insulin release from pancreatic β cells by managing potassium efflux. It shares two binding sites with sulfonylureas and also has a unique site, indicating overlapping mechanisms of action. With a rapid onset and a 4-7 hour duration, it effectively...
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Psychosexual Stages of Personality: Oral01:16

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The oral stage is the initial phase of Sigmund Freud's theory of psychosexual development, occurring from birth to approximately 12 to 18 months. During this period, the infant's mouth serves as the primary source of pleasure, with actions such as sucking, chewing, biting, and drinking playing a crucial role in reducing tension. These activities are essential not only for nourishment but also for the infant's psychological and emotional satisfaction.
Weaning, typically occurring...
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Oral Hypoglycemic Agents: Sulfonylureas01:17

Oral Hypoglycemic Agents: Sulfonylureas

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Sulfonylureas are oral hypoglycemic agents utilized in treating type 2 diabetes. They are characterized by their unique sulfonylurea chemical structure. The family of sulfonylureas is divided into generations. First-generation sulfonylureas, including tolbutamide (Orinase), chlorpropamide (Diabinese), and tolazamide (Tolinase), trigger insulin release from pancreatic β cells and enhance peripheral tissues' insulin sensitivity. The second-generation members, such as glipizide...
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Assessing Body Temperature - Oral01:14

Assessing Body Temperature - Oral

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Here are the steps to accurately measure oral temperature using an electronic thermometer:
Step 1:
Start by practicing proper hand hygiene to prevent the spread of microorganisms.
Step 2:
Take the thermometer out of the charging unit, switch it on, and wait for the ready sign.
Step 3:
Gently slide the probe cover until a click is heard. This simple action prevents cross-contamination and ensures the correct placement of the probe cover.
Step 4:
Instruct the patient to open their mouth and place...
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Non-Oral Extravascular Drug Absorption Routes01:15

Non-Oral Extravascular Drug Absorption Routes

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Non-oral extravascular routes, which encompass sublingual, buccal, topical, intramuscular, and inhalation methods, primarily utilize passive diffusion to transport drugs into the systemic circulation. The absorption rates and effectiveness of these routes depend on the drug's physicochemical properties, as well as the patient's anatomical and pathophysiological state.
Lipophilic drugs that are stable at salivary pH (6) and exhibit minimal binding to the oral mucosa are absorbed more...
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Related Experiment Video

Updated: Jan 21, 2026

Modeling Oral-Esophageal Squamous Cell Carcinoma in 3D Organoids
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Deep visual detection system for oral squamous cell carcinoma.

Kainat Akram1, Muhammad Aslam1, Talha Waheed1

  • 1Department of Computer Science, University of Engineering and Technology, Lahore, 54000, Pakistan.

Scientific Reports
|January 19, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a Deep Visual Detection System (DVDS) using EfficientNetB3 for automated Oral Squamous Cell Carcinoma (OSCC) detection from histopathological images. The system achieved high accuracy, demonstrating potential for faster and more consistent OSCC diagnosis to improve patient outcomes.

Keywords:
Binary classificationCancer detectionComputer-aided diagnosisEfficientNetB3Health risksMulticlass detectionOral squamous cell carcinoma

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Computational Pathology

Background:

  • Oral Squamous Cell Carcinoma (OSCC) poses a significant health challenge, necessitating accurate and timely diagnosis.
  • Traditional histopathological methods for OSCC diagnosis are subjective and time-consuming.
  • Advancements in Artificial Intelligence (AI) offer potential for objective and efficient analysis of histopathological images.

Purpose of the Study:

  • To develop and evaluate an automated Deep Visual Detection System (DVDS) for Oral Squamous Cell Carcinoma (OSCC) detection.
  • To compare the performance of different deep learning models (EfficientNetB3, DenseNet121, ResNet50) for OSCC classification.
  • To assess the system's reliability and robustness in diagnosing OSCC from histopathological images.

Main Methods:

  • Utilized three Convolutional Neural Network (CNN) models: EfficientNetB3, DenseNet121, and ResNet50.
  • Trained and evaluated models on two public datasets: Kaggle Oral Cancer Detection and NDB-UFES.
  • Employed data augmentation, image preprocessing, and training strategies like EarlyStopping and ReduceLROnPlateau.

Main Results:

  • EfficientNetB3 demonstrated superior performance, achieving 97.05% accuracy in binary classification and 97.16% accuracy in multi-class classification.
  • The system exhibited high precision, recall, F1-score, and specificity across both datasets.
  • DenseNet121 and ResNet50 showed significantly lower accuracy compared to EfficientNetB3.

Conclusions:

  • The Deep Visual Detection System (DVDS) powered by EfficientNetB3 shows high reliability for OSCC diagnosis.
  • The AI-driven approach can significantly streamline diagnostic workflows and aid pathologists.
  • This technology holds strong potential for clinical deployment to support early intervention and enhance patient care.