Hannah Sophie Muti

According to our database, Hannah Sophie Muti authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Benchmarking foundation models as feature extractors for weakly-supervised computational pathology.

Peter Neidlinger, Omar S. M. El Nahhas, Hannah Sophie Muti, Tim Lenz, Michael Hoffmeister, Hermann Brenner, Marko van Treeck, Rupert Langer, Bastian Dislich, Hans Michael Behrens, Christoph Röcken, Sebastian Foersch, Daniel Truhn, Antonio Marra, Oliver Lester Saldanha, Jakob Nikolas Kather

CoRR, 2024

Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance.

Jan Moritz Niehues, Gustav Müller-Franzes, Yoni Schirris, Sophia J. Wagner, Michael Jendrusch, Matthias Kloor, Alexander T. Pearson, Hannah Sophie Muti, Katherine Jane Hewitt, Gregory Patrick Veldhuizen, Laura Zigutyte, Daniel Truhn, Jakob Nikolas Kather

Comput. Biol. Medicine, 2024

2023

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides.

Omar S. M. El Nahhas, Chiara Maria Lavinia Loeffler, Zunamys I. Carrero, Marko van Treeck, Fiona R. Kolbinger, Katherine Jane Hewitt, Hannah Sophie Muti, Mara Graziani, Qinghe Zeng, Julien Calderaro, Nadina Ortiz-Brüchle, Tanwei Yuan, Michael Hoffmeister, Hermann Brenner, Alexander Brobeil, Jorge S. Reis-Filho, Jakob Nikolas Kather

CoRR, 2023

2022

Classical mathematical models for prediction of response to chemotherapy and immunotherapy.

Narmin Ghaffari Laleh, Chiara Maria Lavinia Loeffler, Julia Grajek, Katerina Stanková, Alexander T. Pearson, Hannah Sophie Muti, Christian Trautwein, Heiko Enderling, Jan Poleszczuk, Jakob Nikolas Kather

PLoS Comput. Biol., 2022

Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474.

Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y. Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman David Bülow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J. Brinker, Firas Khader, Daniel Truhn, Nadine T. Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, Jakob Nikolas Kather

Medical Image Anal., 2022

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y. Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman David Bülow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J. Brinker, Firas Khader, Daniel Truhn, Nadine T. Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, Jakob Nikolas Kather

Medical Image Anal., 2022

2021

Deep Learning for interpretable end-to-end survival (E-ESurv) prediction in gastrointestinal cancer histopathology.

Narmin Ghaffari Laleh, Amelie Echle, Hannah Sophie Muti, Katherine Jane Hewitt, Volkmar Schulz, Jakob Nikolas Kather

Proceedings of the MICCAI Workshop on Computational Pathology, 2021