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Itsaso Vitoria Fernández de Castillo. Biomedical Engineer (2022) and Master in Machine Learning for Health (2023). She completed her Master's thesis on the characterisation of mouse models of polycystic kidney disease using light-sheet microscopy images, specialising in medical imaging.
Nowadays, she belongs to the Core Visual platform of Tecnalia's Digital unit. Her contribution to this platform is research in the field of automatic analysis of medical images through advanced machine learning techniques. Currently, her research is focused on the development of a tool to support the early diagnosis of melanoma in primary care.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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Collaborations and top research areas from the last five years
Research output
- 1 Article
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In-depth 3D exploration of autosomal dominant polycystic kidney disease through light sheet fluorescence microscopy
Delgado-Rodriguez, P., Vitoria, I., Ríos-Muñoz, G. R., Bardia, L., Lamanna-Rama, N., Nicolas-Saenz, L., Sporring, J., Soto-Montenegro, M. L., Aldabe, R., Colombelli, J. & Muñoz-Barrutia, A., Dec 2025, In: Scientific Reports. 15, 1, 40843.Research output: Contribution to journal › Article › peer-review
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