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Updated: Jun 22, 2025
The Three-Dimensional Human Skin Reconstruct Model: a Tool to Study Normal Skin and Melanoma Progression
Published on: August 3, 2011
Artificial intelligence and skin melanoma
1Dermatology Department, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, United Kingdom.
Abstract:
Melanoma is the deadliest skin cancer, presenting typically with changing pigmented areas and usually treated with surgical removal. As benign cutaneous pigmented lesions are very common in all populations, it can be challenging to identify which areas should be cut out or left untreated. Delayed treatment in melanoma increases the risk of death, but it is not possible to remove all lesions. Dermatoscopy uses polarized light and can be used to help distinguish melanomas from benign lesions. Dermatoscopy images with a confirmed diagnosis can be used to develop artificial intelligence (AI) as a medical device (AIaMD) tool. This contribution discusses the utilization of AI in melanoma management and describes an AIaMD tool used in current UK clinical practice on more than 80,000 patients. This is a springboard for discussing the scope, risks, and mitigations for future AI use by all clinicians involved in managing people with melanoma.
Insights
Artificial intelligence (AI) aids in melanoma management by distinguishing cancerous lesions from benign ones using dermatoscopy images. An AI medical device (AIaMD) tool is used in UK practice, improving melanoma diagnosis and treatment planning.
Area of Science:
- Dermatology
- Medical Artificial Intelligence (AI)
- Oncology
Background:
- Melanoma, the deadliest skin cancer, presents diagnostic challenges due to common benign pigmented lesions.
- Timely diagnosis and treatment are critical, but removing all lesions is impractical.
- Dermatoscopy aids in differentiating melanoma from benign lesions.
Purpose of the Study:
- To discuss the role of AI in melanoma management.
- To describe an AI-as-a-medical-device (AIaMD) tool utilized in UK clinical practice.
- To explore the scope, risks, and mitigations for future AI implementation in melanoma care.
Main Methods:
- Development of an AIaMD tool using dermatoscopy images with confirmed diagnoses.
- Clinical implementation of the AIaMD tool in UK healthcare settings.
- Analysis of AIaMD tool performance and impact on patient management.
Main Results:
- The AIaMD tool has been used in current UK clinical practice on over 80,000 patients.
- AI assists in distinguishing between melanoma and benign pigmented lesions.
- Data from extensive use provides a basis for future AI development and deployment.
Conclusions:
- AI demonstrates significant potential in enhancing melanoma diagnosis and management.
- The discussed AIaMD tool is a validated resource in current clinical practice.
- Further exploration of AI's scope, risks, and mitigation strategies is essential for widespread adoption.
