检索结果-内蒙古大学图书馆

Multimodal Interpretable Data-Driven Models for Early Prediction of Antimicrobial Multidrug Resistance Using Multivariate Time-Series

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Martínez-Agüero, Sergio Marques, Antonio G. Mora-Jiménez, Inmaculada Alvárez-Rodríguez, Joaquín Soguero-Ruiz, Cristina Department of Signal Theory and Communications Telematics and Computing Systems Rey Juan Carlos University Madrid Fuenlabrada28942 Spain Intensive Care Department University Hospital of Fuenlabrada Madrid Fuenlabrada28942 Spain

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 valuable tool for clinical prediction, their fusion with other data modalities can possibly result in more thorough insights and more accurate results. Deep neural networks (DNNs) have emerged as fundamental tools for identifying and defining underlying patterns in the healthcare domain. However, fundamental improvements in interpretability are needed for DNN models to be widely used in the clinical setting. In this study, we present an approach built on a collection of interpretable multimodal data-driven models that may anticipate and understand the emergence of antimicrobial multidrug resistance (AMR) germs in the intensive care unit (ICU) of the University Hospital of Fuenlabrada (Madrid, Spain). The profile and initial health status of the patient are modeled using static variables, while the evolution of the patient’s health status during the ICU stay is modeled using several MTS, including mechanical ventilation and antibiotics intake. The multimodal DNNs models proposed in this paper include interpretable principles in addition to being effective at predicting AMR and providing an explainable prediction support system for AMR in the ICU. Furthermore, our proposed methodology based on multimodal models and interpretability schemes can be leveraged in additional clinical problems dealing with EHR data, broadening the impact and applicability of our results. © 2024, CC BY.

关键词： Intensive care units

Tri-Band Endfire Antenna Array with Wide Angles of Beam-Scanning Capability for 5G mmWave Mobile Communication

学校读者我要写书评

暂无评论

Tri-Band Endfire Antenna Array with Wide Angles of Beam-Scan...

2023 IEEE International Workshop on Technologies for Defense and Security, TechDefense 2023

作者： Zidour, Ali Ayad, Mouloud Alibakhshikenari, Mohammad Basherlou, Haleh Jahanbakhsh Parchin, Naser Ojaroudi See, Chan Hwang University of m'Hamed Bougara Faculty of Technology Department of Electrical Systems Engineering Boumerdes Algeria University of Bouira Faculty of Sciences and Applied Sciences Department of Electrical Systems Bouira Algeria Universidad Carlos Iii de Madrid Leganés Department of Signal Theory and Communications Madrid Spain Edinburgh Napier University School of Computing Engineering and the Built Environment Edinburgh United Kingdom

ISBN: (纸本)9798350319392

In this paper, a novel multiband phased array antenna with endfire radiation pattern is designed at millimeter-wave (mmWave) frequency bands for 5G mobile applications. The proposed antenna element is a compact quasi-Yagi with a modified dipole driver to generate multiband operation, arranged on low-loss RO4003C materiel. The antenna array achieves excellent performance and covers wide frequency ranges of (24.15-29.8 GHz), (36.2-50 GHz) to support 5G NR bands;26, 28, 39 and the new allocated 48 GHz. The array can exhibit a maximum realized gain from 8.4 dBi to 11.8 dBi. Meanwhile, wide beam-scanning angles from - 68° to 65° at 28 GHz, from 40° to 41° at 39 GHz, and from - 33° to 35° at 48 GHz are realized. © 2023 IEEE.

关键词： Millimeter waves

LM-IGTD: a 2D image generator for low-dimensional and mixed-type tabular data to leverage the potential of convolutional neural networks

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Gómez-Martínez, Vanesa Lara-Abelenda, Francisco J. Peiro-Corbacho, Pablo Chushig-Muzo, David Granja, Conceição Soguero-Ruiz, Cristina Department of Signal Theory and Communications Telematics and Computing Systems Rey Juan Carlos University Madrid28943 Spain Norwegian Centre for E-health Research University Hospital of North Norway Tromsø9008 Norway

Tabular data have been extensively used in different knowledge domains. Convolutional neural networks (CNNs) have been successfully used in many applications where important information about data is embedded in the order of features (images), outperforming predictive results of traditional models. Recently, several researchers have proposed transforming tabular data into images to leverage the potential of CNNs and obtain high results in predictive tasks such as classification and regression. In this paper, we present a novel and effective approach for transforming tabular data into images, addressing the inherent limitations associated with low-dimensional and mixed-type datasets. Our method, named Low Mixed-Image Generator for Tabular Data (LM-IGTD), integrates a stochastic feature generation process and a modified version of the IGTD. We introduce an automatic and interpretable end-to-end pipeline, enabling the creation of images from tabular data. A mapping between original features and the generated images is established, and post hoc interpretability methods are employed to identify crucial areas of these images, enhancing interpretability for predictive tasks. An extensive evaluation of the tabular-to-image generation approach proposed on 12 low-dimensional and mixed-type datasets, including binary and multi-class classification scenarios. In particular, our method outperformed all traditional ML models trained on tabular data in five out of twelve datasets when using images generated with LM-IGTD and CNN. In the remaining datasets, LM-IGTD images and CNN consistently surpassed three out of four traditional ML models, achieving similar results to the fourth model. © 2024, CC BY.

关键词： Image classification

Interpretable Machine Learning Models for PISA Results in Mathematics

学校读者我要写书评

暂无评论

SSRN

SSRN 2024年

作者： Gómez-Talal, Ismael Bote-Curiel, Luis Rojo-Álvarez, José Luis Department of Signal Theory and Communications and Telematic Systems and Computation Rey Juan Carlos Univeristy Camino del Molino s/n Fuenlabrada Madrid28943 Spain D!lemmaLab Ldt. Camino del Molino s/n Fuenlabrada Madrid28943 Spain

The Programme for International Student Assessment (PISA) 2022 provides a canvas to explore educational achievements across the globe. Our study focuses on Spain’s adolescent mathematical performance using advanced Machine Learning (ML) techniques. Through meticulous preprocessing of the PISA dataset, we categorized students into low, medium, and high proficiency levels and employed various binary classification models to discern predictive patterns. In addition, a stacking meta-model integrating the strengths of eight distinct models was developed to enhance prediction accuracy. Our results demonstrate that the meta-model outperforms individual models in predicting student performance across various proficiency levels, consistently showing superior metrics in precision, recall, and AUC scores. We adopted the Shapley Additive exPlanations (SHAP) method to demystify the model decisions, highlighting significant predictors such as grade repetition, access to digital devices, and extracurricular math classes. The findings spotlight the potential for targeted educational strategies. We also introduce an interactive dashboard, harnessing Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction and enabling a granular view of the educational landscape. The study concludes with a strategic roadmap for future research, emphasizing the need for longitudinal analysis and expansion of the dashboard predictive capabilities, thereby contributing to an informed, adaptive educational system that can respond proactively to the diverse needs of learners. © 2024, The Authors. All rights reserved.

关键词： Additives

Multibeam Compact Dual Reflectarray Antenna for High-Throughput Satellites in Ka-Band

学校读者我要写书评

暂无评论

Multibeam Compact Dual Reflectarray Antenna for High-Through...

European Conference on Antennas and Propagation, EuCAP

作者： Daniel Martinez-de-Rioja Eduardo Martinez-de-Rioja Yolanda Rodriguez-Vaqueiro Antonio Pino Carlos Mosquera Jose A. Encinar Giovanni Toso Information Processing and Telecommunications Center Universidad Politécnica de Madrid Madrid Spain Department of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos Fuenlabrada Spain AtlantTic Research Center Universidade de Vigo Vigo Spain Antenna and Sub-Millimeter Wave Section Electromagnetics Division European Space Agency ESTEC Noordwijk The Netherlands

This contribution describes the design of a dual-reflector multibeam antenna based on a parabolic polarizing main reflector with a flat reflectarray subreflector. This antenna concept is proposed to produce multiple beams in orthogonal CP for enabling broadband satellite communications in Ka-band. The antenna generates two orthogonal beams per feed at transmit (19.7 GHz) and receive (29.5 GHz) frequencies in Ka-band, which would make it possible to reduce by half the number of conventional reflector antennas required onboard the satellite to produce the same multispot coverage. The antenna generates a set of high-gain circularly polarized beams when illuminated by dual-linearly polarized feed-horns, which avoids the use of linear-to-circular polarizers in the feed-chains.

关键词：

Preliminary Simulations of Spherical Reflectarrays in Dual Configuration for Satellite Antennas in Ka-Band

学校读者我要写书评

暂无评论

Preliminary Simulations of Spherical Reflectarrays in Dual C...

European Conference on Antennas and Propagation, EuCAP

作者： Daniel Martinez-De-Rioja Yolanda Rodriguez-Vaqueiro Antonio Pino Eduardo Martinez-De-Rioja Jose A. Encinar Manuel Arrebola Giovanni Toso Information Processing and Telecommunications Center Universidad Politécnica de Madrid Madrid Spain AtlanTTic Research Center for Telecommunication Technologies Universidade de Vigo Vigo Spain Dept. of Signal Theory and Communications and Telematic Systems and Computing Universidad Rey Juan Carlos Fuenlabrada Spain Antenna and Sub-Millimeter Wave Section European Space Agency ESTEC Electromagnetics Division Noordwijk The Netherlands

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

In this contribution, the design of spherical reflectarray antennas is proposed to achieve a compromise between parabolic and spherical surfaces. The spherical surface simplifies the folding mechanism of the antenna, while the printed elements on the reflectarray surface are designed to correct the spherical aberration, improving the focusing of the spherical surface and providing the electrical performance of a parabolic reflector antenna. The focusing and scanning capabilities of spherical reflectarrays are evaluated and the implementation of spherical reflectarrays in dual antenna configurations is proposed to provide further compact antenna solutions.

关键词： Antenna measurements Satellite antennas Satellites Focusing Europe Reflector antennas Antennas and propagation Ka-band Antenna radiation patterns

Explainable Artificial Intelligence Techniques for Irregular Temporal Classification of Multidrug Resistance Acquisition in Intensive Care Unit Patients

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Escudero-Arnanz, Óscar Soguero-Ruiz, Cristina Álvarez-Rodríguez, Joaquín Marques, Antonio G. Department of Signal Theory and Communications Telematics and Computing Systems Rey Juan Carlos University Camino del Molino 5 Fuenlabrada Madrid28942 Spain University Hospital of Fuenlabrada Camino del Molino 2 Fuenlabrada Madrid28942 Spain

Antimicrobial Resistance represents a significant challenge in the Intensive Care Unit (ICU), where patients are at heightened risk of Multidrug-Resistant (MDR) infections—pathogens resistant to multiple antimicrobial agents. This study introduces a novel methodology that integrates Gated Recurrent Units (GRUs) with advanced intrinsic and post-hoc interpretability techniques for detecting the onset of MDR in patients across time. Within interpretability methods, we propose Explainable Artificial Intelligence (XAI) approaches to handle irregular Multivariate Time Series (MTS), introducing Irregular Time Shapley Additive Explanations (IT-SHAP), a modification of Shapley Additive Explanations designed for irregular MTS with Recurrent Neural Networks focused on temporal outputs. Our methodology aims to identify specific risk factors associated with MDR in ICU patients. GRU with Hadamard’s attention demonstrated high initial specificity and increasing sensitivity over time, correlating with increased nosocomial infection risks during prolonged ICU stays. XAI analysis, enhanced by Hadamard attention and IT-SHAP, identified critical factors such as previous non-resistant cultures, specific antibiotic usage patterns, and hospital environment dynamics. These insights suggest that early detection of at-risk patients can inform interventions such as preventive isolation and customized treatments, significantly improving clinical outcomes. The proposed GRU model for temporal classification achieved an average Receiver Operating Characteristic Area Under the Curve of 78.27 ± 1.26 over time, indicating strong predictive performance. In summary, this study highlights the clinical utility of our methodology, which combines predictive accuracy with interpretability, thereby facilitating more effective healthcare interventions by professionals. © 2024, CC BY.

关键词： Intensive care units

Haros graphs: an exotic representation of real numbers

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Calero-Sanz, Jorge Luque, Bartolo Lacasa, Lucas Departamento de Matematica Aplicada a la Ingenieria Aeroespacial ETSIAE Universidad Politecnica de Madrid Madrid Spain Signal and Communications Theory and Telematic Systems and Computing Rey Juan Carlos University Madrid Spain Palma de Mallorca Spain

This paper introduces Haros graphs, a construction which provides a graph-theoretical representation of real numbers in the unit interval reached via paths in the Farey binary tree. We show how the topological structure of Haros graphs yields a natural classification of the reals numbers into a hierarchy of families. To unveil such classification, we introduce an entropic functional on these graphs and show that it can be expressed, thanks to its fractal nature, in terms of a generalised de Rham curve. We show that this entropy reaches a global maximum at the reciprocal of the Golden number and otherwise displays a rich hierarchy of local maxima and minima that relate to specific families of irrationals (noble numbers) and rationals, overall providing an exotic classification and representation of the reals numbers according to entropic principles. We close the paper with a number of conjectures and outline a research programme on Haros graphs. Copyright © 2022, The Authors. All rights reserved.

关键词： Binary trees

On the degree distribution of Haros graphs

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Calero-Sanz, Jorge Departamento de Matemática Aplicada a la Ingeniería Aeroespacial ETSI Aeronáutica y del Espacio Universidad Politécnica de Madrid Madrid Spain Signal and Communications Theory and Telematic Systems and Computing Rey Juan Carlos University Madrid Spain

Haros graphs is a graph-theoretical representation of real numbers in the unit interval. The degree distribution of the Haros graphs provides information regarding the topological structure and the associated real number. This article provides a comprehensive demonstration of a conjecture concerning the analytical formulation of the degree distribution. Specifically, a theorem outlines the relationship between Haros graphs, the corresponding continued fraction of its associated real number, and the subsequent symbolic paths in the Farey binary Tree. Moreover, an expression continuous and piece-wise linear in subintervals defined by Farey fractions can be derived from an additional conclusion for the degree distribution of Haros graphs. Copyright © 2022, The Authors. All rights reserved.

关键词： Complex networks