collaborators

10 papers

eess.SP2026

Benchmarking ECG FMs: A Reality Check Across Clinical Tasks

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

The 12-lead electrocardiogram (ECG) is a long-standing diagnostic tool. Yet machine learning for ECG interpretation remains fragmented, often limited to narrow tasks or datasets. F…

eess.SP2025

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

Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff

Background: Neoplasms are a major cause of mortality globally, where early diagnosis is essential for improving outcomes. Current diagnostic methods are often invasive, expensive,…

eess.SP2025

Estimation of Cardiac and Non-cardiac Diagnosis from Electrocardiogram Features

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Ensuring timely and accurate diagnosis of medical conditions is paramount for effective patient care. Electrocardiogram (ECG) signals are fundamental for evaluating a patient's car…

eess.SP2025

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

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Laboratory value represents a cornerstone of medical diagnostics, but suffers from slow turnaround times, and high costs and only provides information about a single point in time.…

eess.SP2025

Abnormality Prediction and Forecasting of Laboratory Values from Electrocardiogram Signals Using Multimodal Deep Learning

Juan Miguel Lopez Alcaraz, Nils Strodthoff

This study investigates the feasibility of using electrocardiogram (ECG) data combined with basic patient metadata to estimate and monitor prompt laboratory abnormalities. We use t…

cs.LG2025

Explaining Time Series Classification Predictions via Causal Attributions

Juan Miguel Lopez Alcaraz, Nils Strodthoff

Despite the excelling performance of machine learning models, understanding their decisions remains a long-standing goal. Although commonly used attribution methods from explainabl…