• A knowledge model for the development of a framework for hypnogram construction 

      Fernández-Leal, Ángel; Cabrero-Canosa, Mariano; Mosqueira-Rey, E.; Moret-Bonillo, Vicente (Elsevier BV, 2017-02-15)
      [Abstract] We describe a proposal of a knowledge model for the development of a framework for hypnogram construction from intelligent analysis of pulmonology and electrophysiological signals. Throughout the twentieth ...
    • A Systematic and Generalizable Approach to the Heuristic Evaluation of User Interfaces 

      Alonso Ríos, David; Mosqueira-Rey, E.; Moret-Bonillo, Vicente (Taylor & Francis, 2018-01-24)
      [Abstract]: Heuristic evaluation is one of the most actively used techniques for analyzing usability, as it is quick and inexpensive. This technique is based on following a given set of heuristics, which are typically ...
    • A systematic approach to API usability: Taxonomy-derived criteria and a case study 

      Mosqueira-Rey, E.; Alonso Ríos, David; Moret-Bonillo, Vicente; Fernández-Varela, Isaac; Álvarez-Estévez, Diego (Elsevier B.V., 2018-05)
      [Abstract]: CONTEXT. The currently existing literature about Application Program Interface (API) usability is heterogeneous in terms of goals, scope, and audience; and its connection to accepted definitions of usability ...
    • A Taxonomy-Based Usability Study of an Intelligent Speed Adaptation Device 

      Alonso Ríos, David; Mosqueira-Rey, E.; Moret-Bonillo, Vicente (Taylor & Francis Inc., 2014-04-04)
      [Abstract] Usability studies are often based on ad hoc definitions of usability. These studies can be difficult to generalize, they might have a steep learning curve, and there is always the danger of being inconsistent ...
    • Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach 

      Mosqueira-Rey, E.; Hernández-Pereira, Elena; Bobes-Bascarán, José; Alonso Ríos, David; Pérez-Sánchez, Alberto; Fernández-Leal, Ángel; Moret-Bonillo, Vicente; Vidal-Ínsua, Yolanda; Vázquez-Rivera, Francisca (Springer Nature, 2023-11)
      [Abstract]: Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning models. The problem is a data bottleneck, i.e. the difficulty ...
    • Quantum Computing for Dealing with Inaccurate Knowledge Related to the Certainty Factors Model 

      Moret-Bonillo, Vicente; Magaz Romero, Samuel; Mosqueira-Rey, E. (MDPI, 2022)
      [Abstract] In this paper, we illustrate that inaccurate knowledge can be efficiently implemented in a quantum environment. For this purpose, we analyse the correlation between certainty factors and quantum probability. We ...