SOURCE-LINKED INTELLIGENCE
Novel health care strategies for melanoma in children, adolescents and young adults
gression of melanoma in CAYA will be performed through different omic methods, and a novel taxonomy of CAYA melanoma will be generated. 2) MELCAYA will also develop image-based robust and trustworthy machine learning tools and a pan-European second-opinion platform for better diagnosis specifically designed for CAYA. 3) Moreover, the validation of minimally and non-invasive disruptive tools based on artificial intelligence and volatilomics detection from exhaled breath and skin will lead to earlier detection and more accurate prognosis of melanoma in CAYA. 4) Finally, through the evidence gathered, MELCAYA will design and implement public health strategies and will actively involve patients and the general population. The results of MELCAYA will maximize its impact by making its data and results accessible and re-usable through integration into UNCAN.eu. This action is part of the Cancer Mission cluster of projects on ‘‘Understanding""." melanoma, children, adolescents, congenital nevus, exposome, volatilomics,
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 8013218.54
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T01:21:06.728Z. This is not the publication date.