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

Gross Anatomy of the Stomach01:16

Gross Anatomy of the Stomach

1.4K
The human stomach is a vital part of the digestive system, performing multiple functions. It is located within the peritoneum, a serous membrane that lines the abdominal cavity. The stomach plays a central role in processing food substances and interacts with other digestive organs through coordinated digestive processes. The stomach has a characteristic J-shape and is divided into four main regions. The cardia is the first section where the esophagus connects to the stomach and is the entry...
1.4K
Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

161
This lesson explores three gastrointestinal imaging techniques: radionuclide testing, colonic transit studies, and virtual colonoscopy.
Radionuclide Testing
Radionuclide testing is a sophisticated medical technique for assessing gastrointestinal motility. It focuses on gastric emptying and colonic transit time. Radioactive markers track the movement of food through the digestive system, providing insights into gastrointestinal disorders.
In gastric emptying studies, a meal's liquid and...
161
Classification of Illness01:17

Classification of Illness

8.0K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.0K
Stomach Histology01:26

Stomach Histology

1.8K
The stomach comprises several layers that work together to facilitate digestion and protect the organ. The outermost layer is called the serosa, which provides support and protection to the stomach. The muscularis externa layer is responsible for the mechanical breakdown of food by contracting and moving the stomach. The submucosa layer, located beneath the muscularis externa, contains connective tissue, blood vessels, nerves, and glands that secrete mucus and other substances essential for...
1.8K

You might also read

Related Articles

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

Sort by
Same author

Empowering Prediction of Resting Energy Expenditure in Free-Living Settings by AI Tools: Application of a Population-Specific Equation from Saudi Arabia.

Nutrients·2026
Same author

RADAI: A Deep Learning-Based Classification of Lung Abnormalities in Chest X-Rays.

Diagnostics (Basel, Switzerland)·2025
Same author

FCN-PD: An Advanced Deep Learning Framework for Parkinson's Disease Diagnosis Using MRI Data.

Diagnostics (Basel, Switzerland)·2025
Same author

SLA-MLP: Enhancing Sleep Stage Analysis from EEG Signals Using Multilayer Perceptron Networks.

Diagnostics (Basel, Switzerland)·2024
Same author

Optimizing 1D-CNN-Based Emotion Recognition Process through Channel and Feature Selection from EEG Signals.

Diagnostics (Basel, Switzerland)·2023
Same author

Brain Tumor Segmentation from MRI Images Using Handcrafted Convolutional Neural Network.

Diagnostics (Basel, Switzerland)·2023

Related Experiment Video

Updated: Sep 27, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

537

Deep Feature Fusion and Optimization-Based Approach for Stomach Disease Classification.

Farah Mohammad1, Muna Al-Razgan2

  • 1Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia.

Sensors (Basel, Switzerland)
|April 12, 2022
PubMed
Summary

This study introduces a deep learning method for diagnosing stomach diseases from endoscopic images. The automated approach achieves 99.8% accuracy, improving early detection and reducing diagnostic time.

Keywords:
deep featuresdisease classificationfeatures optimizationstomach disease

More Related Videos

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

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

Published on: April 14, 2023

2.7K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.4K

Related Experiment Videos

Last Updated: Sep 27, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

537
Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
05:56

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

Published on: April 14, 2023

2.7K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.4K

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Computational Biology

Background:

  • Stomach cancer is a leading cause of mortality, necessitating early diagnosis for effective treatment.
  • Manual diagnosis of stomach diseases from endoscopic images is time-consuming and requires expert interpretation.
  • Existing automated methods face challenges like feature similarity and extraction, limiting diagnostic accuracy.

Purpose of the Study:

  • To develop an automated, accurate, and efficient method for classifying stomach diseases using endoscopic images.
  • To enhance the early diagnosis of stomach cancer, thereby reducing mortality rates.
  • To overcome limitations of current automated diagnostic techniques in medical image analysis.

Main Methods:

  • A deep learning model was developed, incorporating data augmentation for increased dataset size.
  • Deep transfer learning using Inception v3 and DenseNet-201 models was employed for feature extraction.
  • Extracted features were fused, optimized using a modified dragonfly algorithm, and classified with machine learning algorithms.

Main Results:

  • The proposed deep learning method achieved a high accuracy of 99.8% on a combined stomach disease dataset.
  • The integration of deep feature extraction, fusion, and optimization significantly improved classification performance.
  • Comparative analysis demonstrated superior accuracy compared to existing state-of-the-art techniques.

Conclusions:

  • The proposed deep learning approach offers a highly accurate and efficient solution for automated stomach disease classification.
  • This method has the potential to significantly aid in the early and reliable diagnosis of stomach pathologies.
  • Further research can explore broader applications of this technique in medical image analysis and disease detection.