Resumen/Abstract
Join us for an engaging talk on AI and Explainable AI (XAI) in Healthcare. Dr Claudia Mazo will present cutting-edge research projects on breast cancer detection, histological image analysis, epilepsy surgeries, and the creation of histological atlases. Learn how AI drives innovation in healthcare while addressing the critical need for transparency and explainability. The talk will also cover key principles of Reproducibility and Transparency in AI, including best practices for data and algorithm selection, common training pitfalls, and strategies to enhance model reproducibility and interpretability. If you're looking to deepen your understanding of AI in healthcare and build more reliable models, this is a session you won’t want to miss! Profesor proponente EPS: Marcos Escudero.
Curriculum ponente
Dr. Claudia Mazo holds a double degree PhD in Engineering with an emphasis on Computer Sciences from the University of Valle (Cali-Colombia) and a PhD in Production and Computing from the University of León (León-Spain). From 2017 to 2018 she worked in Vicomtech (San Sebastian-Spain) in the eHealth and biomedical applications area. From 2018 to 2021 she holds a Marie Sklodowska-Curie Postdoctoral Fellowship at University College Dublin and Oncomark Ltd (Dublin-Ireland), gaining extensive experience in academia and industry. From 2021 to 2022 she was a research fellow at University College Dublin (Dublin-Ireland) working on AI to develop advanced diagnostic tools to identify those breast and prostate cancer patients with early-stage disease that can be spared aggressive treatment. She was a member of the ACM-FCA (Association for Computing Machinery - Future of Computing Academy) from 2020 to 2022. Since 2019, she has been an Ad Honorem lecturer at Universidad del Valle (Cali-Colombia) working on different research projects and student supervision. Since 2022, she has been an assistant professor at the School of Computing of Dublin City University (Dublin-Ireland). Dr. Mazo's research interests include Artificial Intelligence, e-Health, Bioinformatics, and Medical-Data Science. She has authored and co-authored +26 peer-reviewed journal articles and +12 conference abstracts, which reflect her active contributions to the field. She has supervised, co-supervised, and mentored undergraduate, Master, and PhD students in Colombia and Ireland. In addition to her academic roles, she is a committee member of the cost action CA22103 – A Comprehensive Network Against Brain Cancer (Net4Brain) and a member of Global BioImaging, Latin America Bioimaging, and Euro-Bioimaging
Escuela Politécnica Superior | Universidad Autónoma de Madrid | Francisco Tomás y Valiente, 11 | 28049 Madrid | Tel.: +34 91 497 2222 | e-mail: informacion.eps@uam.es
