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Andreas Dominik

Observed name: Dominik, Andreas
ORCID: 0000-0002-9368-0812
Observed ORCID: 0000-0002-9368-0812
OpenAlex ID: A5060290595
Using Deep Gated RNN with a Convolutional Front End for End:to:End Classification of Heart Sound
2016 · Christian Thomae, Andreas Dominik · Computing in cardiology · 50
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Decreases in heart rate variability are associated with postoperative complications in hip fracture patients
2017 · Gernot Ernst, Leiv Otto Watne, et al. · PLoS ONE · 36
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Continuous fields: Enhanced in-vehicle anomaly detection using machine learning models
2020 · Florian Fenzl, Roland Rieke, et al. · Simulation Modelling Practice and Theory · 20
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Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: a software engineering perspective
2021 · Christopher Schölzel, Valeria Blesius, et al. · npj Systems Biology and Applications · 17
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In-vehicle detection of targeted CAN bus attacks
2021 · Florian Fenzl, Roland Rieke, et al. · International Conference on Availability, Reliability and Security (ARES) · 15
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Can Electrocardiogram Classification be Applied to Phonocardiogram Data? :: An Analysis Using Recurrent Neural Networks
2016 · Christopher Scholzel, Andreas Dominik · Computing in cardiology · 12
Low Heart Rate Variability Predicts Stroke and Other Complications in the First Six Postoperative Months After a Hip Fracture Operation
2021 · Gernot Ernst, Leiv Otto Watne, et al. · Frontiers in Cardiovascular Medicine · 11
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HRT assessment reviewed: a systematic review of heart rate turbulence methodology
2020 · Valeria Blesius, Christopher Schölzel, et al. · Physiological Measurement · 11
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Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: A software engineering perspective
2019 · Christopher Schölzel, Valeria Blesius, et al. · bioRxiv (Cold Spring Harbor Laboratory) · 9
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Countering reproducibility issues in mathematical models with software engineering techniques: A case study using a one-dimensional mathematical model of the atrioventricular node
2021 · Christopher Schölzel, Valeria Blesius, et al. · PLoS ONE · 8
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Cross-Platform Availability of Smartphone Sensors for Depression Indication Systems: Mixed-Methods Umbrella Review
2025 · Johannes Leimhofer, Milica Petrovic, et al. · Interactive Journal of Medical Research · 7
Towards an automated approach for smart sterility test examination
2022 · Clemens Dierks, Robert Söldner, et al. · SLAS TECHNOLOGY · 6
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An Understandable, Extensible, and Reusable Implementation of the Hodgkin-Huxley Equations Using Modelica
2020 · Christopher Schölzel, Valeria Blesius, et al. · Frontiers in Physiology · 6
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Modeling Biology in Modelica: The Human Baroreflex
2015 · Christopher Schölzel, Alexander Goesmann, et al. · Linköping electronic conference proceedings · 5
Mo|E A Communication Service Between Modelica Compilers and Text Editors
2017 · Nicola Justus, Christopher Schölzel, et al. · Linköping electronic conference proceedings · 4
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Recognition of Abnormalities in Phonocardiograms for Computer:Assisted Diagnosis of Heart Failures
2016 · Simon Hofmann, Volker Gross, et al. · Computing in cardiology · 4
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Comparability of Heart Rate Turbulence Methodology: 15 Intervals Suffice to Calculate Turbulence Slope – A Methodological Analysis Using PhysioNet Data of 1074 Patients
2022 · Valeria Blesius, Christopher Schölzel, et al. · Frontiers in Cardiovascular Medicine · 2
RHRT: An R package to assess Heart Rate Turbulence
2021 · Valeria Blesius, Andreas Dominik · The Journal of Open Source Software · 2
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Individual-Level Modeling of Depressive Symptom Severity Using Smartphone and Wearable Data: Time-Aware 1-Year Study With Feature-Group Contributions
2026 · Simon Schreynemackers, Johannes Leimhofer, et al. · JMIR Formative Research · 1
Can 1-Year Smartphone and Wearable Data allow Individual-level Modeling of Depressive Symptom Severity?
2026 · Ulrich Hegerl, Simon Schreynemackers, et al. · Research Square · 1
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MoVE A Standalone Modelica Vector Graphics Editor
2017 · Nicola Justus, Christopher Schölzel, et al. · Linköping electronic conference proceedings · 1
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Modeling Temporal Associations Between Mobile Sensing Features and Depressive Symptom Severity in Adults with Depressive Disorders: A Proof-of-Concept Study. (Preprint)
2026 · Johannes Leimhofer, Simon Schreynemackers, et al.
Methods Protocol: Identifying Objective Mobile Sensing Markers of Depressive Symptoms Using Individualized and Federated Learning
2026 · Leimhofer, Johannes, Schreynemackers, Simon, et al.
Individualized and Shared Learning for Predicting Daily Depressive Symptom Severity from Multimodal Smartphone and Wearable Data: A Longitudinal Evaluation of Information Sharing
2026 · Johannes Leimhofer, Simon Schreynemackers, et al. · SSRN Electronic Journal
PFAM Protein Families Dataset for Machine Learning
2023 · Dominik, Andreas · Zenodo (CERN European Organization for Nuclear Research)
Works count: 28
Citation count: 228
H-index: 9
I10-index: 8
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