Zobrazeno 21 - 30
of 58
pro vyhledávání: '"Kerstin Ritter"'
Autor:
Marc-Andre Schulz, Stefan Hetzer, Fabian Eitel, Susanna Asseyer, Lil Meyer-Arndt, Tanja Schmitz-Hübsch, Judith Bellmann-Strobl, James H. Cole, Stefan M. Gold, Friedemann Paul, Kerstin Ritter, Martin Weygandt
SummaryClinical and neuroscientific studies suggest a link between psychological stress and reduced brain health - in healthy humans and patients with neurological disorders. However, it is unclear which neural pathways mediate between stress and bra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::515c39e780be2c3d3f22092fd34833f8
https://doi.org/10.1101/2022.12.19.521098
https://doi.org/10.1101/2022.12.19.521098
Autor:
Christoph Koch, Matthias Weidlich, Volker Markl, Lars Grunske, Dagmar Kainmüller, Alexander Reinefeld, Peter Eisert, Ulf Leser, Florian Schintke, Knut Reinert, Timo Kehrer, Odej Kao, Tilmann Rabl, Nicole Schweikardt, Henning Meyerhenke, Patrick Hostert, Birte Kehr, Claudia Draxl, Marcus Hilbrich, Björn Scheuermann, Kerstin Ritter
Publikováno v:
Datenbank-Spektrum
Today’s scientific data analysis very often requires complex Data Analysis Workflows (DAWs) executed over distributed computational infrastructures, e.g., clusters. Much research effort is devoted to the tuning and performance optimization of speci
Autor:
Malte Klingenberg, Didem Stark, Fabian Eitel, Mohamad Habes, Kerstin Ritter, for the Alzheimer's Disease Neuroimaging Initiative (ADNI)
Introduction: Although machine learning classifiers have been frequently used to detect Alzheimer's disease (AD) based on structural brain MRI data, potential bias with respect to sex and age has not yet been addressed. Here, we examine a state-of-th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1219ad9f56451e337b0e50f8dbe93d3c
https://doi.org/10.21203/rs.3.rs-1964110/v1
https://doi.org/10.21203/rs.3.rs-1964110/v1
Autor:
Carina Nina Vorisek, Caroline Stellmach, Paula Josephine Mayer, Sophie Anne Ines Klopfenstein, Dominik Martin Bures, Anke Diehl, Maike Henningsen, Kerstin Ritter, Sylvia Thun
BACKGROUND Resources are increasingly spent on artificial intelligence (AI) solutions for medical applications aiming to improve diagnosis, treatment and prevention of diseases. While the need for transparency and reduction of bias in data and algori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1834de110213985d92a6a701ccd40b43
https://doi.org/10.2196/preprints.41089
https://doi.org/10.2196/preprints.41089
Autor:
Carina Nina Vorisek, Caroline Stellmach, Paula Josephine Mayer, Sophie Anne Ines Klopfenstein, Dominik Martin Bures, Anke Diehl, Maike Henningsen, Kerstin Ritter, Sylvia Thun
Publikováno v:
Journal of Medical Internet Research.
Autor:
Pooja Subramaniam, Tabea Kossen, Kerstin Ritter, Anja Hennemuth, Kristian Hildebrand, Adam Hilbert, Jan Sobesky, Michelle Livne, Ivana Galinovic, Ahmed A. Khalil, Jochen B. Fiebach, Dietmar Frey, Vince I. Madai
Publikováno v:
Medical Image Analysis
Deep learning requires large labeled datasets that are difficult to gather in medical imaging due to data privacy issues and time-consuming manual labeling. Generative Adversarial Networks (GANs) can alleviate these challenges enabling synthesis of s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9aa78606b3f9041b0d9513b20562f1d8
https://hdl.handle.net/21.11116/0000-000A-119D-221.11116/0000-000A-119F-0
https://hdl.handle.net/21.11116/0000-000A-119D-221.11116/0000-000A-119F-0
Autor:
Silvan Hornstein, Moritz Seiler, Valerie Hoffman, Benjamin W Nelson, Kirstin Aschbacher, Kerstin Ritter, Kevin Hilbert
Heart Rate Variability (HRV) is a putative biological mechanism and marker of depression, which can be measured with low costs and in naturalistic settings. Therefore, applying machine learning (ML) on HRV data, could be a promising path to predict a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e1b8c725399e710e60a2b4864139844
https://doi.org/10.31234/osf.io/9z3pr
https://doi.org/10.31234/osf.io/9z3pr
Machine learning studies have shown that various phenotypes can be predicted from structural and functional brain images. However, in most such studies, prediction performance ranged from moderate to disappointing. It is unclear whether prediction pe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a006bb3481a981942eada66b58cf77aa
https://doi.org/10.1101/2022.02.23.481601
https://doi.org/10.1101/2022.02.23.481601
Autor:
Dorothee Kübler, Sophie Katharina Wellmann, Jakob Kaminski, Cornelia Skowronek, Gerd-Helge Schneider, Wolf-Julian Neumann, Kerstin Ritter, Andrea Kühn
Publikováno v:
Parkinsonism & related disorders 94, 89-95 (2022). doi:10.1016/j.parkreldis.2021.12.002
INTRODUCTION Subthalamic DBS in Parkinson's disease has been associated with cognitive decline in few cases. Volume reduction of the nucleus basalis of Meynert (NBM) seems to precede cognitive impairment in Parkinson's disease. In this retrospective
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffef7567ca51fc75261eb9d2d2839b66
https://pub.dzne.de/record/163419
https://pub.dzne.de/record/163419
Autor:
Claudia, Chien, Moritz, Seiler, Fabian, Eitel, Tanja, Schmitz-Hübsch, Friedemann, Paul, Kerstin, Ritter
Background: Lack of easy-to-interpret disease activity prediction methods in early MS can lead to worse patient prognosis. Objectives: Using machine learning (multiple kernel learning - MKL) models, we assessed the prognostic value of various clinica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8285d8670796febc173b238294e27e6f