Abstract
Background: The ultra-rare nature of melanoma in children, adolescents, and young adults poses significant challenges to the development and implementation of effective prevention and diagnostic strategies. This article delves into the ELSIs surrounding these strategies, placing particular emphasis on the transformative potential of AI-driven tools and applications. Methods: Using an exploratory sequential mixed methods approach, this study integrated a PICO-guided literature review and qualitative insights from two focus groups. The review included 26 peer-reviewed articles published in English from January 2019 to January 2024, addressing ELSIs in melanoma, rare diseases, and AI in dermatology. Focus groups included a March 2024 session in Berlin with 15 stakeholders (patients, caregivers, advocates, healthcare professionals) and a November 2024 online session with 5 interdisciplinary experts. Results: Six key priorities for healthcare policies emerged: addressing cultural factors, such as the glorification of tanned skin; enhancing professional training for accurate diagnosis; balancing the risks of overdiagnosis and underdiagnosis; promoting patient autonomy through transparent communication; reducing inequalities to ensure equitable access to care; and making ethical and legal use of AI in healthcare. Conclusion: These priorities provide a comprehensive framework for advancing the prevention and diagnosis of melanoma in children, adolescents, and young adults, leveraging AI technologies while prioritizing equitable and patient-centered healthcare delivery.
| Original language | English |
|---|---|
| Pages (from-to) | 321-N/A |
| Journal | HEALTHCARE |
| Volume | 13 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Leadership and Management
- Health Policy
- Health Informatics
- Health Information Management
Keywords
- artificial intelligence (AI)
- childhood melanoma (CHM)
- early diagnosis
- ethical
- legal and social implications (ELSIs)
- prevention
- ultra-rare cancer
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