B. Rieck

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Weisfeiler and Leman go Machine Learning: The Story so far pdf

Yaron Lipman, Nils M. Kriege, Martin Grohe, 2021, ArXiv.

Graph Kernels: State-of-the-Art and Future Challenges

K. Borgwardt, F. Llinares-López, B. Rieck, 2020 .

Topological Methods for fMRI Data

K. Borgwardt, N. Turk-Browne, Guy Wolf, 2020 .

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

K. Borgwardt, Bastian Alexander Rieck, Maximilian Brackmann, 2020, bioRxiv.

Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis

Karsten M. Borgwardt, K. Borgwardt, Bastian Alexander Rieck, 2020, Travel Medicine and Infectious Disease.

E arly P rediction of S epsis in the ICU using M achine L earning : A S ystematic R eview .

K. Borgwardt, C. Jutzeler, Michael Moor, 2020 .

Weisfeiler and Leman go Machine Learning: The Story so far

Nils M. Kriege, K. Borgwardt, Y. Lipman, 2021, ArXiv.

Multigranular single-cell analysis reveals inflammatory interactions driving

Guy Wolf, Smita Krishnaswamy, M. Hirn, 2022 .

G2 stem cells orchestrate time-directed, long-range coordination of calcium signaling during skin epidermal regeneration

Smita Krishnaswamy, Caroline E. Hendry, Dhananjay Bhaskar, 2022, bioRxiv.

G2 stem cells orchestrate time-directed, long-range coordination of calcium signaling during skin epidermal regeneration

Smita Krishnaswamy, Caroline E. Hendry, Dhananjay Bhaskar, 2021, bioRxiv.

Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis pdf

Karsten M. Borgwardt, Gabriel Brändle, Nina Wiedemann, 2020, ArXiv.

Multiscale PHATE identifies multimodal signatures of COVID-19

Daniel B. Burkhardt, S. Farhadian, A. Iwasaki, 2022, Nature Biotechnology.

Early prediction of circulatory failure in the intensive care unit using machine learning

Karsten M. Borgwardt, Stephanie L. Hyland, Martin Faltys, 2020, Nature Medicine.

Accelerating detection of lung pathologies with explainable ultrasound image analysis

Karsten M. Borgwardt, Michael Moor, Jannis Born, 2021 .

Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review

Karsten M. Borgwardt, K. Borgwardt, Bastian Alexander Rieck, 2020, Frontiers in Medicine.

Early prediction of circulatory failure in the intensive care unit using machine learning

Stephanie L. Hyland, G. Rätsch, K. Borgwardt, 2020, Nature Medicine.

Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra

Karsten Borgwardt, Adrian Egli, Bastian Rieck, 2020, Bioinform..

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

K. Borgwardt, Bastian Alexander Rieck, Maximilian Brackmann, 2020, Nature Medicine.

Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design

C. Jutzeler, B. Rieck, S. Brüningk, 2020, ArXiv.

Weisfeiler and Leman go Machine Learning: The Story so far

Nils M. Kriege, K. Borgwardt, Y. Lipman, 2021, ArXiv.

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning pdf

Michael Moor, Karsten Borgwardt, Max Horn, 2021, ArXiv.

ACCELERATING COVID-19 DIFFERENTIAL DIAGNOSISWITH EXPLAINABLE ULTRASOUND IMAGE ANALYSIS: AN AI TOOL

A. Aujayeb, G. Brändle, B. Rieck, 2021, Ultrasound in Medicine & Biology.

Improved MALDI-TOF MS based antimicrobial resistance prediction through hierarchical stratification

K. Borgwardt, A. Egli, C. Weis, 2022, bioRxiv.

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning

K. Borgwardt, Bastian Alexander Rieck, Maximilian Brackmann, 2022, Nature Medicine.