8 citations · 17 across the 7 of their papers we have counts for
7 papers
ECG-LLM -- training and evaluation of domain-specific large language models for electrocardiography
Lara Ahrens, Wilhelm Haverkamp, Nils Strodthoff
Domain-adapted open-weight large language models (LLMs) offer promising healthcare applications, from queryable knowledge bases to multimodal assistants, with the crucial advantage…
Multi-Window Temporal Analysis for Enhanced Arrhythmia Classification: Leveraging Long-Range Dependencies in Electrocardiogram Signals
Tiezhi Wang, Wilhelm Haverkamp, Nils Strodthoff
Objective. Arrhythmia classification from electrocardiograms (ECGs) suffers from high false positive rates and limited cross-dataset generalization, particularly for atrial fibrill…
Explainable and externally validated machine learning for neurocognitive diagnosis via electrocardiograms
Juan Miguel Lopez Alcaraz, Ebenezer Oloyede, David Taylor +2
Background: Electrocardiogram (ECG) analysis has emerged as a promising tool for detecting physiological changes linked to non-cardiac disorders. Given the close connection between…
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…
Prospects for AI-Enhanced ECG as a Unified Screening Tool for Cardiac and Non-Cardiac Conditions -- An Explorative Study in Emergency Care
Nils Strodthoff, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp
Current deep learning algorithms designed for automatic ECG analysis have exhibited notable accuracy. However, akin to traditional electrocardiography, they tend to be narrowly foc…
Using explainable AI to investigate electrocardiogram changes during healthy aging -- from expert features to raw signals
Gabriel Ott, Yannik Schaubelt, Juan Miguel Lopez Alcaraz +2
Cardiovascular diseases remain the leading global cause of mortality. Age is an important covariate whose effect is most easily investigated in a healthy cohort to properly disting…