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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/221135
Time-Varying Topological Descriptors for Cardiac Disease Diagnosis
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Abstract
Cardiac diseases are among the most common illnesses in the world, and data scientists have created a wide range of tools to contribute to their detection and diagnosis. In particular, topological data analysis has been used to work with medical imaging and specifically with cardiac magnetic resonance images. This project introduces the use of time-varying topological descriptors along a cardiac cycle and applies them for disease diagnosis. The methods used aim to develop the relationship between topological data analysis and temporal data. We also intend to contribute to the simplification, interpretability and improvement of a computational approach to cardiac disease diagnosis, which usually involves costly calculations of radiomics or potential black boxes.
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Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona. Any: 2025. Tutor: Carles Casacuberta i Laura Igual Muñoz
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FERRERAS ALEGRE, Jon. Time-Varying Topological Descriptors for Cardiac Disease Diagnosis. [consulted: 8 of June of 2026]. Available at: https://hdl.handle.net/2445/221135