• Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process 

  ARRAZOLA, PEDRO JOSE; Aristimuño, Patxi Xabier; Saez de Buruaga, Mikel (Elsevier, 2023)

  Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data-driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing ...

• Long term EIT based compliance monitoring in COVID-19 patients 

  Isasa Reinoso, Imanol (De Gruyter, 2021)

  The COVID-19 is a viral infection that causes respiratory complications. Infected lungs often present ground glass opacities, thus suggesting that medical imaging technologies could provide useful information for the disease ...

• Foveal Remodeling of Retinal Microvasculature in Parkinson’s Disease 

  Barrenechea, Maitane; Erramuzpe Aliaga, Asier; Ayala, Unai; Romero-Bascones, David (Frontiers, 2021)

  Background: Retinal microvascular alterations have been previously described in Parkinson’s disease (PD) patients using optical coherence tomography angiography (OCT-A). However, an extensive description of retinal vascular ...

• Real-Time, Model-Agnostic and User-Driven Counterfactual Explanations Using Autoencoders 

  Labaien Soto, Jokin; Zugasti, Ekhi (MDPI, 2023)

  Explainable Artificial Intelligence (XAI) has gained significant attention in recent years due to concerns over the lack of interpretability of Deep Learning models, which hinders their decision-making processes. To address ...

• Integrated machine learning and probabilistic degradation approach for vessel electric motor prognostics 

  Aizpurua Unanue, Jose Ignacio (Elsevier, 2023)

  In the transition towards more sustainable ships, electric motors (EM) are being used in ship propulsion systems to reduce emissions and increase efficiency. The safe operation of ships is crucial, and prognostics and ...

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