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

Skin Cancer

Skin Cancer

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...

You might also read

Related Articles

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

Sort by

Same author

Improving Risk Stratification for SLNB in Elderly Patients With Melanoma: The SENTINOLD Nomogram.

International journal of dermatology·2026

Same author

Risk of infections in patients with psoriasis treated with biologic agents and new oral small molecules: BIOBADADERM registry.

The Journal of investigative dermatology·2026

Same author

Integrating Advanced Technologies for Environmental Valuation in Legacy Mining Sites: The Role of Digital Twins at Lavrion Technological and Cultural Park.

Sensors (Basel, Switzerland)·2025

Same author

Recurrent status is associated with poor outcomes in cutaneous squamous cell carcinoma.

Journal of the European Academy of Dermatology and Venereology : JEADV·2025

Same author

Identifying potential palaeolithic artificial memory systems via Spatial statistics: Implications for the origin of quantification.

Archaeological and anthropological sciences·2025

Same author

Safety of sonidegib in elderly patients with locally advanced basal cell carcinoma: A multicentre study.

Journal of the European Academy of Dermatology and Venereology : JEADV·2025

Search research articles

Related Experiment Video

Updated: Sep 23, 2025

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

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

Published on: August 18, 2022

Deep Convolutional Neural Support Vector Machines for the Classification of Basal Cell Carcinoma Hyperspectral

Lloyd A Courtenay¹, Diego González-Aguilera¹, Susana Lagüela¹

¹Department of Cartographic and Terrain Engineering, Higher Polytechnic School of Ávila, University of Salamanca, Hornos Caleros 50, 05003 Ávila, Spain.

Journal of Clinical Medicine

|May 14, 2022

Summary

Early detection of basal cell carcinoma, a common skin cancer, is vital. This study shows hyperspectral imaging combined with AI accurately identifies basal cell carcinoma, achieving 90% accuracy.

Keywords:

basal cell carcinoma computational learning convolutional neural networks hyperspectral sensor support vector machines

More Related Videos

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Related Experiment Videos

Last Updated: Sep 23, 2025

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

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

Published on: August 18, 2022

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

Area of Science:

Dermatology and Medical Imaging
Artificial Intelligence in Oncology

Background:

Non-melanoma skin cancer, particularly basal cell carcinoma (BCC), is highly prevalent.
BCC's locally destructive nature underscores the importance of early detection and treatment.
Multispectral imaging and AI offer non-invasive tools for skin cancer diagnosis.

Purpose of the Study:

To differentiate between healthy skin and basal cell carcinoma using hyperspectral imaging signatures.
To evaluate the efficacy of a combined AI approach for BCC detection.

Main Methods:

Utilized hyperspectral imaging to capture spectral signatures of skin tissue.
Employed convolutional neural networks (CNNs) integrated with a support vector machine (SVM) activation layer.
Trained and tested the AI model on hyperspectral data.

Main Results:

Achieved up to 90% accuracy in distinguishing between healthy skin and BCC.
Calculated an area under the receiver operating characteristic curve (AUC) of 0.9.
Demonstrated the potential of AI-powered hyperspectral analysis for BCC classification.

Conclusions:

Hyperspectral imaging combined with CNN-SVM AI models shows significant promise for non-invasive BCC detection.
The developed method offers a high degree of accuracy for early skin cancer identification.
Further validation with larger patient datasets is recommended to enhance clinical applicability.