Listar por autor "Muñiz, Brais"

Mostrando ítems 1-9 de 9

    • A rule-based system for explainable donor-patient matching in liver transplantation 

      Aguado, Felicidad; Cabalar, Pedro; Fandiño, Jorge; Muñiz, Brais; Pérez, Gilberto; Suárez, Francisco (Open Publishing Association, 2019-09)
      [Abstract]: In this paper we present web-liver, a rule-based system for decision support in the medical domain, focusing on its application in a liver transplantation unit for implementing policies for donor-patient matching. ...

    • A System for Explainable Answer Set Programming 

      Cabalar, Pedro; Fandinno, Jorge; Muñiz, Brais (Open Publishing Association, 2020-09-19)
      [Abstract] We present xclingo, a tool for generating explanations from ASP programs annotated with text and labels. These annotations allow tracing the application of rules or the atoms derived by them. The input of ...

    • Accelerating 3D printing of pharmaceutical products using machine learning 

      Ong, Jun Jie; Muñiz, Brais; Gaisford, Simon; Cabalar, Pedro; Basit, Abdul W; Pérez, Gilberto; Goyanes, Álvaro (Elsevier, 2022)
      [Abstract] Three-dimensional printing (3DP) has seen growing interest within the healthcare industry for its ability to fabricate personalized medicines and medical devices. However, it may be burdened by the lengthy ...

    • aspBEEF: Explaining Predictions Through Optimal Clustering 

      Cabalar, Pedro; Martín, Rodrigo; Muñiz, Brais; Pérez, Gilberto (MDPI AG, 2020-08-28)
      [Abstract] In this paper we introduce aspBEEF, a tool for generating explanations for the outcome of an arbitrary machine learning classifier. This is done using Grover’s et al. framework known as Balanced English ...

    • Generating Commonsense Explanations with Answer Set Programming 

      Muñiz, Brais (2024)
      [Abstract] In this thesis, we explore the notion of commonsense explanation in the context of Artificial Intelligence by extending the formalism of Answer Set Programming (ASP) with formal annotations. To this aim, we ...

    • M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines 

      Elbadawi, Moe; Muñiz, Brais; Gavins, Francesca K.H.; Ong, Jun Jie; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2020-11)
      [Abstract]: Artificial intelligence (AI) has the potential to reshape pharmaceutical formulation development through its ability to analyze and continuously monitor large datasets. Fused deposition modeling (FDM) ...

    • Machine learning predicts 3D printing performance of over 900 drug delivery systems 

      Muñiz, Brais; Elbadawi, Moe; Ong, Jun Jie; Pollard, Thomas; Song, Zhe; Gaisford, Simon; Pérez, Gilberto; Basit, Abdul W; Cabalar, Pedro; Goyanes, Álvaro (Elsevier B.V., 2021-09)
      [Abstract]: Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy ...

    • Model Explanation via Support Graphs 

      Cabalar, Pedro; Muñiz, Brais (Cambridge Univeristy Press, 2024-02)
      [Absctract]: In this note, we introduce the notion of support graph to define explanations for any model of a logic program. An explanation is an acyclic support graph that, for each true atom in the model, induces a proof ...

    • Predicting pharmaceutical inkjet printing outcomes using machine learning 

      Carou-Senra, Paola; Ong, Jun Jie; Muñiz, Brais; Seoane-Viaño, Iria; Rodríguez-Pombo, Lucía; Cabalar, Pedro; Álvarez-Lorenzo, Carmen; Basit, Abdul W; Pérez, Gilberto; Goyanes, Álvaro (Elsevier B.V., 2023)
      [Abstract]: Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex ...