Nils Strodthoff

Carl von Ossietzky Universität Oldenburg — Germany

Medicine · Health Sciences

27h-index4.0kcitations130works2.82yr avg
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Research Topics

ECG Monitoring and Analysis(32), Quantum Chromodynamics and Particle Interactions(25), High-Energy Particle Collisions Research(19), Particle physics theoretical and experimental studies(14), Machine Learning in Healthcare(10)

Publications131 total

Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches
Biomedical Signal Processing and Control·2026
MIMIC-III-Ext-PPG: A PPG Benchmark Dataset for Cardiorespiratory Analysis
PhysioNet·2026Open Access
MIMIC-III-Ext-PPG: A PPG Benchmark Dataset for Cardiorespiratory Analysis
PhysioNet·2026Open Access
Multi-window temporal analysis for enhanced arrhythmia classification: leveraging long-range dependencies in electrocardiogram signals
Physiological Measurement·2026Open Access
Multi-window temporal analysis for enhanced arrhythmia classification: leveraging long-range dependencies in electrocardiogram signals
Physiological Measurement·2026Open Access
A Multimodal Deep Learning Framework for Predicting ICU Deterioration: Integrating ECG Waveforms with Clinical Data and Clinician Benchmarking
ArXiv.org·2026Open Access
A Multimodal Deep Learning Framework for Predicting ICU Deterioration: Integrating ECG Waveforms with Clinical Data and Clinician Benchmarking
arXiv (Cornell University)·2026Open Access
Benchmarking machine learning for bowel sound pattern classification – From tabular features to pretrained models
PLoS ONE·2026Open Access
Machine Learning Versus Simple Clinical Models for Cochlear Implant Outcome Prediction
Audiology Research·2025Open Access
Abnormality prediction and forecasting of laboratory values from electrocardiogram signals using multimodal deep learning
Scientific Reports·2025Open Access
Explaining Time Series Classification Predictions via Causal Attributions
2025
A systematic evaluation of uncertainty quantification techniques in deep learning: a case study in photoplethysmography signal analysis
arXiv (Cornell University)·2025Open Access
ECG-LLM -- training and evaluation of domain-specific large language models for electrocardiography
arXiv (Cornell University)·2025Open Access
Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks
Machine Learning Health·2025Open Access
Explainable and externally validated machine learning for neurocognitive diagnosis via ECGs
General Psychiatry·2025Open Access
Benchmarking ECG Foundational Models: A Reality Check Across Clinical Tasks
arXiv (Cornell University)·2025Open Access
Predicting Chest Radiograph Findings from Electrocardiograms Using Interpretable Machine Learning
arXiv (Cornell University)·2025Open Access
Generalizable deep learning for photoplethysmography-based blood pressure estimation—A benchmarking study
Machine Learning Health·2025· 2 citedOpen Access
Transforming sepsis management: AI-driven innovations in early detection and tailored therapies
Critical Care·2025· 14 citedOpen Access
Explainable machine learning for neoplasms diagnosis via electrocardiograms: an externally validated study
Cardio-Oncology·2025· 2 citedOpen Access
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Frequent Co-authors

Jan M. Pawlowski(11), Wojciech Samek(9), Lorenz von Smekal(8), Mario Mitter(5), Temesgen Mehari(5), Wilhelm Haverkamp(5), Patrick Wagner(4), Anton K. Cyrol(4), Markus Wenzel(4), J. Wambach(4), Johanna Vielhaben(4), Tobias Schaeffter(3), Klaus‐Robert Müller(3), Jackie Ma(3), Juan Miguel Lopez Alcaraz(3), Stefan Blücher(3), Ralf-Arno Tripolt(2), Kazuhiko Kamikado(2), Maximilian Springenberg(2), Annika Frommholz(2)