Juan Miguel Lopez Alcaraz

According to our database, Juan Miguel Lopez Alcaraz authored at least 19 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

A Multimodal Deep Learning Framework for Predicting ICU Deterioration: Integrating ECG Waveforms with Clinical Data and Clinician Benchmarking.

Juan Miguel Lopez Alcaraz, Xicoténcatl López Moran, Erick Dávila Zaragoza, Claas Händel, Richard Koebe, Wilhelm Haverkamp, Nils Strodthoff

CoRR, January, 2026

2025

Towards actionable hypotension prediction - predicting catecholamine therapy initiation in the intensive care unit.

Richard Koebe, Noah Saibel, Juan Miguel Lopez Alcaraz, Simon Schäfer, Nils Strodthoff

CoRR, October, 2025

Benchmarking ECG Foundational Models: A Reality Check Across Clinical Tasks.

M. A Al-Masud, Juan Miguel Lopez Alcaraz, Nils Strodthoff

CoRR, September, 2025

Predicting Chest Radiograph Findings from Electrocardiograms Using Interpretable Machine Learning.

Julia Matejas, Olaf Zurawski, Nils Strodthoff, Juan Miguel Lopez Alcaraz

CoRR, September, 2025

Explainable and externally validated machine learning for neuropsychiatric diagnosis via electrocardiograms.

Juan Miguel Lopez Alcaraz, Ebenezer Oloyede, David Taylor, Wilhelm Haverkamp, Nils Strodthoff

CoRR, February, 2025

Enhancing clinical decision support with physiological waveforms - A multimodal benchmark in emergency care.

Juan Miguel Lopez Alcaraz, Hjalmar Bouma, Nils Strodthoff

Comput. Biol. Medicine, 2025

Explaining Time Series Classification Predictions via Causal Attributions.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Proceedings of the 37th IEEE International Conference on Tools with Artificial Intelligence, 2025

2024

Explainable machine learning for neoplasms diagnosis via electrocardiograms: an externally validated study.

Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff

CoRR, 2024

Electrocardiogram-based diagnosis of liver diseases: an externally validated and explainable machine learning approach.

Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff

CoRR, 2024

CardioLab: Laboratory Values Estimation and Monitoring from Electrocardiogram Signals - A Multimodal Deep Learning Approach.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

CoRR, 2024

Estimation of Cardiac and Non-cardiac Diagnosis from Electrocardiogram Features.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

CoRR, 2024

CardioLab: Laboratory Values Estimation from Electrocardiogram Features - An Exploratory Study.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

CoRR, 2024

MDS-ED: Multimodal Decision Support in the Emergency Department - a Benchmark Dataset for Diagnoses and Deterioration Prediction in Emergency Medicine.

Juan Miguel Lopez Alcaraz, Hjalmar Bouma, Nils Strodthoff

CoRR, 2024

CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

CoRR, 2024

2023

Diffusion-based conditional ECG generation with structured state space models.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Comput. Biol. Medicine, September, 2023

Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models.

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Trans. Mach. Learn. Res., 2023

Cardiac and extracardiac discharge diagnosis prediction from emergency department ECGs using deep learning.

Nils Strodthoff, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp

CoRR, 2023

Uncovering ECG Changes during Healthy Aging using Explainable AI.

Gabriel Ott, Yannik Schaubelt, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff

CoRR, 2023

2022

From Interpretable Filters to Predictions of Convolutional Neural Networks with Explainable Artificial Intelligence.

Shagufta Henna, Juan Miguel Lopez Alcaraz

CoRR, 2022