1 citations · 2 across the 4 of their papers we have counts for
4 papers
Early Detection of Multidrug Resistance Using Multivariate Time Series Analysis and Interpretable Patient-Similarity Representations
Óscar Escudero-Arnanz, Antonio G. Marques, Inmaculada Mora-Jiménez +2
Background and Objectives: Multidrug Resistance (MDR) is a critical global health issue, causing increased hospital stays, healthcare costs, and mortality. This study proposes an i…
Explainable Spatio-Temporal GCNNs for Irregular Multivariate Time Series: Architecture and Application to ICU Patient Data
Óscar Escudero-Arnanz, Cristina Soguero-Ruiz, Antonio G. Marques
In this paper, we present XST-GCNN (eXplainable Spatio-Temporal Graph Convolutional Neural Network), a novel architecture for processing heterogeneous and irregular Multivariate Ti…
Explainable Artificial Intelligence Techniques for Irregular Temporal Classification of Multidrug Resistance Acquisition in Intensive Care Unit Patients
Óscar Escudero-Arnanz, Cristina Soguero-Ruiz, Joaquín Álvarez-Rodríguez +1
Antimicrobial Resistance represents a significant challenge in the Intensive Care Unit (ICU), where patients are at heightened risk of Multidrug-Resistant (MDR) infections-pathogen…
Multimodal Interpretable Data-Driven Models for Early Prediction of Antimicrobial Multidrug Resistance Using Multivariate Time-Series
Sergio Martínez-Agüero, Antonio G. Marques, Inmaculada Mora-Jiménez +2
Electronic health records (EHR) is an inherently multimodal register of the patient's health status characterized by static data and multivariate time series (MTS). While MTS are a…