Andreas Kist

Assistant professor

Friedrich-Alexander Universität Erlangen-Nürnberg

Germany

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About

Dr. Andreas Kist is an Assistant Professor at Friedrich-Alexander-Universität Erlangen-Nürnberg in Germany. His research spans various areas including implicit neural representations, deep learning applications in medical imaging, and the development of mobile health applications for respiratory disease management. He has published extensively on topics such as laryngeal aerodynamics and the use of large language models for analyzing electronic health records.

Articles (18)

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2025

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2025

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2025

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2024

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2023

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2022

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2022

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2021

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2021

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2021

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2020

Collaborators (6)

Michael Döllinger

University Hospital Erlangen

GERMANY

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Katharina Breininger

Professor

Julius-Maximilians-Universität Würzburg

GERMANY

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Ruben Portugues

Assistant Professor

Technical University of Munich

GERMANY

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Rita Patel

Associate Professor

Indiana State University

UNITED STATES

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Nicole Y. K. Li-Jessen

CANADA

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Leonard Steinbacher

Technical University of Munich

GERMANY

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Andreas Kist

Research Interests

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About

Articles (18)

Implicit neural representations for laryngeal aerodynamics

EvoVis: Dashboard for Visualizing Evolutionary Neural Architecture Search Algorithms

Predicting semantic segmentation quality in laryngeal endoscopy images

A Mobile Health Application and System Architecture for Respiratory Disease Management: Design Principles, Tool Development and Pilot Usability Test (Preprint)

Unstructured Electronic Health Records of Dysphagic Patients Analyzed by Large Language Models

Implicit neural representations in light microscopy

DeepD3, an open framework for automated quantification of dendritic spines

Towards image-based laryngeal videostroboscopy using deep learning-enabled compressed sensing

Pixel-Based Swallow Measurements: Correcting Nonsquare Pixels

GlottisNetV2: Temporal Glottal Midline Detection Using Deep Convolutional Neural Networks

Impact of Mixed Precision Techniques on Training and Inference Efficiency of Deep Neural Networks

Wearable Prophylaxis Tool for AI-Driven Identification of Early Warning Patterns of Pressure Ulcers

Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care

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

A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis

A cerebellar internal model calibrates a feedback controller involved in sensorimotor control

Interdependencies between acoustic and high-speed videoendoscopy parameters

BAGLS, a multihospital Benchmark for Automatic Glottis Segmentation

Collaborators (6)

Michael Döllinger

Katharina Breininger

Ruben Portugues

Rita Patel

Nicole Y. K. Li-Jessen

Leonard Steinbacher

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