Hendrik Burwinkel

Carl Zeiss (Germany) — Germany

Computer Science · Physical Sciences

8h-index315citations20works0.52yr avg
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Research Topics

Machine Learning in Healthcare(8), Radiomics and Machine Learning in Medical Imaging(7), Ophthalmology and Visual Impairment Studies(4), Advanced Graph Neural Networks(4), Corneal surgery and disorders(3)

Publications20 total

Relative Behavior of Modern Intraocular Lens Power Calculation Formulas Across a Realistic Range of Biometry Values
Clinical ophthalmology·2025Open Access
Evaluation of an artificial intelligence-based intraocular lens calculator
Journal of Cataract & Refractive Surgery·2024· 1 citedOpen Access
Multimodal graph attention network for COVID-19 outcome prediction
Scientific Reports·2023· 25 citedOpen Access
ToxNet: an artificial intelligence designed for decision support for toxin prediction
Clinical Toxicology·2022· 9 citedOpen Access
U-PET: MRI-based Dementia Detection with Joint Generation of Synthetic FDG-PET Images
arXiv (Cornell University)·2022· 1 citedOpen Access
Physics-aware learning and domain-specific loss design in ophthalmology
Medical Image Analysis·2021· 8 cited
AI for Doctors—A Course to Educate Medical Professionals in Artificial Intelligence for Medical Imaging
Healthcare·2021· 38 citedOpen Access
U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome Prediction
arXiv (Cornell University)·2021Open Access
U-GAT: Multimodal Graph Attention Network for COVID-19 Outcome\n Prediction
arXiv (Cornell University)·2021· 1 citedOpen Access
Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification
Artificial Intelligence in Medicine·2021· 13 citedOpen Access
Decision support for toxin prediction using artificial intelligence
mediaTUM (Technical University of Munich)·2021
Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC)
arXiv (Cornell University)·2020· 7 citedOpen Access
Domain-specific loss design for unsupervised physical training: A new\n approach to modeling medical ML solutions
arXiv (Cornell University)·2020· 2 citedOpen Access
Decision Support for Intoxication Prediction Using Graph Convolutional Networks
Lecture notes in computer science·2020Open Access
Domain-Specific Loss Design for Unsupervised Physical Training: A New Approach to Modeling Medical ML Solutions
Lecture notes in computer science·2020Open Access
Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets
arXiv (Cornell University)·2019· 4 citedOpen Access
Multi-modal Graph Fusion for Inductive Disease Classification in\n Incomplete Datasets
arXiv (Cornell University)·2019· 4 citedOpen Access
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
arXiv (Cornell University)·2019· 18 citedOpen Access
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
Lecture notes in computer science·2019· 140 cited
Graph Convolution Based Attention Model for Personalized Disease Prediction
Lecture notes in computer science·2019· 44 cited

Frequent Co-authors

Nassir Navab(18), Seyed‐Ahmad Ahmadi(13), Matthias Keicher(8), Anees Kazi(7), Gerome Vivar(7), David Bani-Harouni(6), Tobias Czempiel(4), Thomas Wendler(4), Andreas Zwergal(4), Shayan Shekarforoush(3), S. Arvind Krishna(3), Shadi Albarqouni(3), Magdalini Paschali(3), Egon Burian(3), Marcus R. Makowski(3), Tobias Zellner(3), Florian Eyer(3), H. Matz(3), Stefan Saur(3), Christoph Hauger(3)