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Miriam Hägele
Miriam Hägele
Bestätigte E-Mail-Adresse bei tu-berlin.de
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Zitiert von
Zitiert von
Jahr
iNNvestigate neural networks!
M Alber, S Lapuschkin, P Seegerer, M Hägele, KT Schütt, G Montavon, ...
J. Mach. Learn. Res. 20 (93), 1-8, 2019
2902019
Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning
F Klauschen, KR Müller, A Binder, M Bockmayr, M Hägele, P Seegerer, ...
Seminars in cancer biology 52, 151-157, 2018
1132018
Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
M Hägele, P Seegerer, S Lapuschkin, M Bockmayr, W Samek, ...
Scientific Reports 10 (1), 1-12, 2020
892020
Morphological and molecular breast cancer profiling through explainable machine learning
A Binder, M Bockmayr, M Hägele, S Wienert, D Heim, K Hellweg, M Ishii, ...
Nature Machine Intelligence 3 (4), 355-366, 2021
552021
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
A Binder, M Bockmayr, M Hägele, S Wienert, D Heim, K Hellweg, ...
arXiv preprint arXiv:1805.11178, 2018
272018
How to iNNvestigate neural network’s predictions!
M Alber, S Lapuschkin, P Seegerer, M Hägele, KT Schütt, G Montavon, ...
42018
EEG correlates of visual recognition while overtly tracking a moving object
M Ušćumlić, M Hägele, B Blankertz
International Workshop on Symbiotic Interaction, 166-171, 2015
32015
68MO Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies
M Hägele, KR Müller, C Denkert, A Schneeweiss, BV Sinn, M Untch, ...
Annals of Oncology 33, S572-S573, 2022
2022
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