During a recent coordination meeting held at the Gijón Campus, the ARTERiA project consortium highlighted the maturity of its research. This work focuses on the analysis of biomedical signals by combining advanced signal processing techniques, artificial intelligence (AI), and Quantum Machine Learning (QML) models.
The project is coordinated by the University of Jaén (UJA) and involves the participation of the University of Oviedo. The teams have evaluated the progress made during the first half of the project, particularly in critical areas such as the detection, classification, and prediction of arrhythmias and valvulopathies.
Significant advancements were presented during the working sessions regarding the optimization of QML models applied to classical systems. Furthermore, progress has been made in signal processing and AI applied to spirometry and adventitious lung sounds, which are crucial for respiratory system evaluation and preventive patient monitoring.
“"The quality and rigor of the research are supported by the solid volume of results already disseminated in high-impact Journal Citation Reports (JCR) publications and prestigious international conferences."
Looking ahead to the second half of the project, researchers are planning integration tasks to transform consolidated scientific knowledge into tangible technological applications. The goal is to materialize these efforts into tools that complement medical diagnosis, bringing the medicine of the future closer to daily practice.
