A full list of publications can be found on ORCID
Selected publications:
M. Wehr et al., RespiraTox – Development of a QSAR model to predict human respiratory irritants, Regulatory Toxicology and Pharmacology, DOI: 10.1016/j.yrtph.2021.105089, 2022
A. Lorenc et al., Clinicians' Views of Patient-initiated Follow-up in Head and Neck Cancer: a Qualitative Study to Inform the PETNECK2 Trial, Clinical Oncology, DOI: 0.1016/j.clon.2021.11.010, 2022
A. Karwath et al., Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis, Lancet, DOI: 10.1016/S0140-6736(21)01638-X, 2021
L. Slater et al., Towards similarity-based differential diagnostics for common diseases, Computers in Biology and Medicine, DOI: 10.1016/j.compbiomed.2021.104360, 2021
K. Bunting et al., Improving the diagnosis of heart failure in patients with atrial fibrillation. Heart (British Cardiac Society), DOI: 10.1136/heartjnl-2020-318557, 2021
E. Carr et al., Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study, BMC Medicine, DOI: 10.1186/s12916-020-01893-3, 2021
H Wu et al., Ensemble learning for poor prognosis predictions: a case study on SARS-CoV2, Journal of the American Medical Informatics Association, DOI: 10.1093/jamia/ocaa295, 2020
M. Köppel et al., Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance, Machine Learning and Knowledge Discovery in Databases, DOI: 10.1007/978-3-030-46133-1_15, 2020
S. Altubai et al., Ontology-based prediction of cancer driver genes, Scientific Reports, DOI: 10.1038/s41598-019-53454-1, 2019
A. Karwath et al., Convolutional Neural Networks for the Identification of Regions of Interest in PET Scans: A Study of Representation Learning for Diagnosing Alzheimer’s Disease, Conference on Artificial Intelligence in Medicine in Europe, DOI: 10.1007/978-3-319-59758-4_36, 2017
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