67 citations · 101 across the 16 of their papers we have counts for
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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,…
Electrocardiogram-based diagnosis of liver diseases: an externally validated and explainable machine learning approach
Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff
Background: Liver diseases present a significant global health challenge and often require costly, invasive diagnostics. Electrocardiography (ECG), a widely available and non-invas…
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…
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…
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.…
Enhancing clinical decision support with physiological waveforms -- a multimodal benchmark in emergency care
Juan Miguel Lopez Alcaraz, Hjalmar Bouma, Nils Strodthoff
Background: AI-driven prediction algorithms have the potential to enhance emergency medicine by enabling rapid and accurate decision-making regarding patient status and potential d…
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…