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

Skin Cancer01:30

Skin Cancer

4.4K
Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
Basal Cell Carcinoma (BCC): BCC is the most common type of skin cancer, accounting for about 80% of cases. It typically develops in...
4.4K
Classification of Illness01:17

Classification of Illness

7.8K
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...
7.8K
Skin Diseases and Disorders01:23

Skin Diseases and Disorders

4.0K
Skin is the first line of defense and encounters a variety of microbes. Some pathogenic strains are often the cause of a broad range of infections of the skin and other body systems. These conditions can affect people of all ages and may have different causes, including genetic factors, infections, autoimmune reactions, environmental factors, and lifestyle choices.
Gram-positive Staphylococcus spp. and Streptococcus spp. are responsible for many of the most common skin infections. However, many...
4.0K

You might also read

Related Articles

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

Sort by
Same author

Optimized disease prediction in healthcare systems using HDBN and CAEN framework.

MethodsX·2025
Same author

Genetic Algorithm-Based Human Mental Stress Detection and Alerting in Internet of Things.

Computational intelligence and neuroscience·2022
Same author

Breast Cancer Pathological Image Classification Based on the Multiscale CNN Squeeze Model.

Computational intelligence and neuroscience·2022
Same author

CNN-Based Cross-Modal Residual Network for Image Synthesis.

BioMed research international·2022
Same author

Cyclic GAN Model to Classify Breast Cancer Data for Pathological Healthcare Task.

BioMed research international·2022
Same author

Appropriate Supervised Machine Learning Techniques for Mesothelioma Detection and Cure.

BioMed research international·2022
Same journal

RETRACTION: Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Facial Emotion Recognition Using a Novel Fusion of Convolutional Neural Network and Local Binary Pattern in Crime Investigation.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Automatic Intelligent System Using Medical of Things for Multiple Sclerosis Detection.

Computational intelligence and neuroscience·2026
Same journal

RETRACTION: Intangible Cultural Heritage Reproduction and Revitalization: Value Feedback, Practice, and Exploration Based on the IPA Model.

Computational intelligence and neuroscience·2026
See all related articles

Related Experiment Video

Updated: Aug 29, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.6K

Skin Diseases Classification Using Hybrid AI Based Localization Approach.

Keshetti Sreekala1, N Rajkumar2, R Sugumar3

  • 1Department of CSE, Mahatma Gandhi Institute of Technology, Hyderabad, Telangana, India.

Computational Intelligence and Neuroscience
|September 8, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces Spectral Centroid Magnitude (SCM) for improved skin cancer classification using deep learning. The enhanced convolutional neural network shows promising results for earlier and more accurate disease detection.

More Related Videos

Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition
09:37

Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition

Published on: August 18, 2022

2.4K
Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
06:08

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

16.9K

Related Experiment Videos

Last Updated: Aug 29, 2025

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.6K
Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition
09:37

Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition

Published on: August 18, 2022

2.4K
Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
06:08

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging

Published on: May 5, 2011

16.9K

Area of Science:

  • Dermatology and Artificial Intelligence
  • Medical Imaging Analysis
  • Computational Pathology

Background:

  • Skin cancer diagnosis relies on visual inspection and dermoscopy, with early detection crucial for patient outcomes.
  • Deep learning algorithms analyzing annotated skin images show promise for skin lesion classification.
  • Accurate disease categorization remains a challenge despite various identification strategies.

Purpose of the Study:

  • To enhance the accuracy of skin cancer detection and classification using advanced computational methods.
  • To introduce a novel feature extraction technique for improved diagnostic capabilities.
  • To evaluate the performance of an enhanced convolutional neural network in identifying skin lesions.

Main Methods:

  • Feature extraction using Spectral Centroid Magnitude (SCM).
  • Application of a median filter during the initial preprocessing stage.
  • Classification of the dataset utilizing an enhanced convolutional neural network (CNN).

Main Results:

  • The developed SCM method and enhanced CNN demonstrated improved outcomes in skin lesion classification.
  • Comparison with current methods indicated enhanced accuracy in disease detection.
  • The preprocessing steps, including median filtering, contributed to the overall performance.

Conclusions:

  • The integration of SCM and enhanced CNN offers a robust approach for early and accurate skin cancer diagnosis.
  • Computer-aided diagnosis, though underutilized, is vital for advancing dermatological diagnostics.
  • Further research and implementation of these AI-driven methods can significantly improve patient care in dermatology.