Author

A. M. Kist

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:cell type annotation· 2 Assay:imaging· 2 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Organism:human· 1

Frequent Co-Authors

A. Schuetzenberger· 1 shared A. Schützenberger· 1 shared J. Zilker· 1 shared L. Martignetti· 1 shared M. Döllinger· 1 shared M. Semmler· 1 shared N. Y. Li-Jessen· 1 shared P. Gomez· 1 shared

Activity by Year

2020-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

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1 shared paperBioengineering

A. Schuetzenberger

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Author profile →

3 papers

Recent·Most cited

Efficient and Explainable Deep Neural Networks for Airway Symptom Detection in Support of Wearable Health Technology

R. Groh, Z. Lei, L. Martignetti, N. Y. Li-Jessen, A. M. Kist

This study develops efficient and explainable DNNs for detecting airway symptoms using mechanoacoustic data, achieving 83.7% accuracy with a low memory footprint.

bioRxiv · Dec 30, 2021Bioengineering

A single latent channel is sufficient for biomedical image segmentation

A. M. Kist, S. Duerr, A. Schuetzenberger, M. Semmler

This paper shows that a single latent channel is sufficient for glottis segmentation using deep neural networks, enabling efficient and clinically applicable models.

bioRxiv · Dec 10, 2021 · PreprintBioengineering

Rethinking glottal midline detection

A. M. Kist, J. Zilker, P. Gomez, A. Schützenberger, M. Döllinger

This study evaluates methods for automatic glottal midline detection using simulations and endoscopic images, finding deep neural networks outperform classical computer vision methods.

bioRxiv · Aug 20, 2020Bioengineering