NEXT-GEN-SOMNUS

New generation machine learning algorithms for the analysis of medical sleep recordings

Grant PID2023-147422OB-I00 funded by:


Latest publications

Performance Analysis of Quantum Support Vector Classifiers and Quantum Neural Networks

[Conference] International Joint Conference on Neural Networks 2025

Villalba-Ferreiro, Tomás; Mosqueira-Rey, Eduardo; Alvarez-Estevez, Diego

This study explores the performance of Quantum Support Vector Classifiers (QSVCs) and Quantum Neural Networks (QNNs) in comparison to classical models for machine learning tasks. We find that quantum models tend to outperform classical approaches as the problem complexity increases, as QNNs exhibit superior performance in higher-complexity tasks due to their increased quantum load. These findings highlight the potential of Quantum Machine Learning (QML) for complex classification problems and provide insights into model selection and optimization strategies.
Multi-Task Deep-Learning for Sleep Event Detection and Stage Classification

[Conference] IEEE Symposium Series on Computational Intelligence

Anido-Alonso, Adriana; Alvarez-Estevez, Diego

A multi-task deep-learning approach, inspired by computer vision's object detection, is proposed to simultaneously detect sleep events and construct hypnograms, streamlining the complex process of polysomnographic sleep analysis.
  • Publication
    • Unified Framework for Implementing Inaccurate Knowledge in Quantum Symbolic Artificial Intelligence Models

    [Conference] 17th International Conference on Agents and Artificial Intelligence

    Mosqueira-Rey, Eduardo; Magaz-Romero, Samuel; Moret-Bonillo Vicente

    We present different models for implementing inaccurate knowledge in quantum computers and propose a unified framework to represent and implement the common features of all of them.
  • Publication

    • Latest news

    • Analyzing the performance of various Quantum Machine Learning models

      10/Jul/2025

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      This year, the International Joint Conference on Neural Networks (IJCNN) took place in Rome, Italy, from June 30th to July 5th. There, Eduardo Mosqueira-Rey (PI in NEXT-GEN-SOMNUS), had the oportunity to present new work about exploring the performance of Quantum Support Vector Classifiers (QSVCs) and Quantum Neural Networks (QNNs) in... [Read More]

    • AI to improve the diagnosis of sleep disorders

      26/Mar/2025

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      Adriana Anido Alonso, a researcher at CITIC (Universidade da Coruña), participated in the IEEE Symposium Series on Computational Intelligence held from March 17 to 20 in Trondheim, Norway. Together with Diego Álvarez Estévez, she presented their work titled “Multi-task deep-learning for sleep event detection and stage classification.” [Read More]