:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Weber, Jana, Weber, Marcel, Alcaraz, Juan Miguel Lopez
Format:	Preprint
Published:	2025
Subjects:	Signal Processing
Online Access:	https://arxiv.org/abs/2508.19390
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explainable machine learning for neoplasms diagnosis via electrocardiograms: an externally validated study
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

Electrocardiogram-based diagnosis of liver diseases: an externally validated and explainable machine learning approach
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

Explainable and externally validated machine learning for neurocognitive diagnosis via electrocardiograms
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2025)

Enhancing clinical decision support with physiological waveforms -- a multimodal benchmark in emergency care
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

Estimation of Cardiac and Non-cardiac Diagnosis from Electrocardiogram Features
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

Abnormality Prediction and Forecasting of Laboratory Values from Electrocardiogram Signals Using Multimodal Deep Learning
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

CardioLab: Laboratory Values Estimation from Electrocardiogram Features - An Exploratory Study
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

Prospects for AI-Enhanced ECG as a Unified Screening Tool for Cardiac and Non-Cardiac Conditions -- An Explorative Study in Emergency Care
by: Strodthoff, Nils, et al.
Published: (2023)

Predicting Chest Radiograph Findings from Electrocardiograms Using Interpretable Machine Learning
by: Matejas, Julia, et al.
Published: (2025)

Benchmarking ECG FMs: A Reality Check Across Clinical Tasks
by: Al-Masud, M A, et al.
Published: (2025)

Using explainable AI to investigate electrocardiogram changes during healthy aging -- from expert features to raw signals
by: Ott, Gabriel, et al.
Published: (2023)

Application of Joint Notch Filtering and Wavelet Transform for Enhanced Powerline Interference Removal in Atrial Fibrillation Electrograms
by: Martinez-Iniesta, Miguel, et al.
Published: (2024)

Classifying active and inactive states of growing rabbits from accelerometer data using machine learning algorithms
by: Mora, Mónica, et al.
Published: (2024)

Towards a more realistic evaluation of machine learning models for bearing fault diagnosis
by: Vieira, João Paulo, et al.
Published: (2025)

A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation
by: Garcia, Manuel, et al.
Published: (2024)

Towards actionable hypotension prediction -- predicting catecholamine therapy initiation in the intensive care unit
by: Koebe, Richard, et al.
Published: (2025)

Radio Stripe-Based Distributed ISAC System with Dynamic Sensing-Communication Reconfiguration
by: Rosabal, Osmel Martínez, et al.
Published: (2026)

The Stationary Wavelet Transform as an Efficient Reductor of Powerline Interference for Atrial Bipolar Electrograms in Cardiac Electrophysiology
by: Martinez-Iniesta, Miguel, et al.
Published: (2024)

Supervised Transfer Learning Framework for Fault Diagnosis in Wind Turbines
by: Weber, Kenan, et al.
Published: (2024)

Damage identification for bridges using machine learning: Development and application to KW51 bridge
by: Qiu, Yuqing, et al.
Published: (2024)

Energy-Efficient Analog Beamforming for RF-WET with Charging Time Constraint
by: Rosabal, Osmel Martínez, et al.
Published: (2023)

A Multimodal Deep Learning Framework for Predicting ICU Deterioration: Integrating ECG Waveforms with Clinical Data and Clinician Benchmarking
by: Alcaraz, Juan Miguel López, et al.
Published: (2026)

Interpretable machine learning for cardiogram-based biometrics
by: Tanasković, Ilija, et al.
Published: (2025)

An Efficient Algorithm Based on Wavelet Transform to Reduce Powerline Noise From Electrocardiograms
by: Rodenas, Juan, et al.
Published: (2024)

Benchmarking deep learning models for bearing fault diagnosis using the CWRU dataset: A multi-label approach
by: Rosa, Rodrigo Kobashikawa, et al.
Published: (2024)

Time Variability of FibrillatoryWaves Energy Predicts Long-Term Outcome of Atrial Fibrillation Concomitant Surgical Ablation
by: Rodenas, Juan, et al.
Published: (2024)

Analog Isolated Multilevel Quantizer for Voltage Sensing while Maintaining Galvanic Isolation
by: Weber, Peter, et al.
Published: (2024)

Efficient machine learning for motion sensing for lighting applications
by: Pijlman, Fetze
Published: (2024)

Active IoT User Detection in Near-Field with Location Information
by: de Jesus, Gabriel Martins, et al.
Published: (2026)

Bayesian quantum sensing using graybox machine learning
by: Youssry, Akram, et al.
Published: (2026)

Spectral Distribution Complexity of the Surface Fibrillatory Waves Predicts Post-Catheter Ablation Relapse in Persistent Atrial Fibrillation
by: Escribano, Pilar, et al.
Published: (2024)

Catheter Ablation Outcome Prediction With Advanced Time-Frequency Features of the Fibrillatory Waves From Patients in Persistent Atrial Fibrillation
by: Escribano, Pilar, et al.
Published: (2024)

Operational machine learning for park-scale irrigation to support urban cooling
by: Koçyiğit, Mesut, et al.
Published: (2025)

Movable Antennas-aided Wireless Energy Transfer for the Internet of Things
by: Rosabal, Osmel Martínez, et al.
Published: (2025)

On the Spectral Efficiency of Movable and Rotary Antenna Arrays under Rician Fading
by: Tominaga, Eduardo Noboro, et al.
Published: (2024)

Distributed MIMO Networks with Rotary ULAs for Indoor Scenarios under Rician Fading
by: Tominaga, Eduardo Noboro, et al.
Published: (2024)

Federated Learning-Distillation Alternation for Resource-Constrained IoT
by: da Silva, Rafael Valente, et al.
Published: (2025)

Age of Information in Multi-Relay Networks with Maximum Age Scheduling
by: de Jesus, Gabriel Martins, et al.
Published: (2025)

Assessing cognitive function among older adults using machine learning and wearable device data: a feasibility study
by: Sakal, Collin, et al.
Published: (2023)

Predicting NOx emissions in Biochar Production Plants using Machine Learning
by: Köppel, Marius, et al.
Published: (2024)