Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images (English)
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- New search for: Alber, Maximilian
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- New search for: Holzinger, Andreas
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https://orcid.org/https://orcid.org/0000-0002-6786-5194
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In:
Artificial Intelligence and Machine Learning for Digital Pathology
: State-of-the-Art and Future Challenges
;
Chapter: 2
;
16-37
;
2020
- Article/Chapter (Book) / Electronic Resource
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Title:Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images
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Additional title:Lect.Notes Computer
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Contributors:Holzinger, Andreas ( editor ) / Goebel, Randy ( editor ) / Mengel, Michael ( editor ) / Müller, Heimo ( editor ) / Seegerer, Philipp ( author ) / Binder, Alexander ( author ) / Saitenmacher, René ( author ) / Bockmayr, Michael ( author ) / Alber, Maximilian ( author ) / Jurmeister, Philipp ( author )
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Published in:Artificial Intelligence and Machine Learning for Digital Pathology : State-of-the-Art and Future Challenges ; Chapter: 2 ; 16-37Lecture Notes in Computer Science ; 12090 ; 16-37
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Publisher:
- New search for: Springer International Publishing
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Place of publication:Cham
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Publication date:2020-06-24
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Size:22 pages
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ISBN:
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ISSN:
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DOI:
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Type of media:Article/Chapter (Book)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents eBook
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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Expectations of Artificial Intelligence for PathologyRegitnig, Peter / Müller, Heimo / Holzinger, Andreas et al. | 2020
- 2
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Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin ImagesSeegerer, Philipp / Binder, Alexander / Saitenmacher, René / Bockmayr, Michael / Alber, Maximilian / Jurmeister, Philipp / Klauschen, Frederick / Müller, Klaus-Robert et al. | 2020
- 3
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Supporting the Donation of Health Records to Biobanks for Medical ResearchPichler, Horst / Eder, Johann et al. | 2020
- 4
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Survey of XAI in Digital PathologyPocevičiūtė, Milda / Eilertsen, Gabriel / Lundström, Claes et al. | 2020
- 5
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Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for BiobanksHartfeldt, Christiane / Huth, Verena / Schmitt, Sabrina / Meinung, Bettina / Schirmacher, Peter / Kiehntopf, Michael / Specht, Cornelia / Hummel, Michael et al. | 2020
- 6
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Black Box Nature of Deep Learning for Digital Pathology: Beyond Quantitative to Qualitative Algorithmic PerformancesHayashi, Yoichi et al. | 2020
- 7
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Towards a Better Understanding of the Workflows: Modeling Pathology Processes in View of Future AI IntegrationKargl, Michaela / Regitnig, Peter / Müller, Heimo / Holzinger, Andreas et al. | 2020
- 8
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OBDEX – Open Block Data Exchange SystemLindequist, Björn / Zerbe, Norman / Hufnagl, Peter et al. | 2020
- 9
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Image Processing and Machine Learning Techniques for Diabetic Retinopathy Detection: A ReviewRahim, Sarni Suhaila / Palade, Vasile / Holzinger, Andreas et al. | 2020
- 10
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Higher Education Teaching Material on Machine Learning in the Domain of Digital PathologyStrohmenger, Klaus / Herta, Christian / Fischer, Oliver / Annuscheit, Jonas / Hufnagl, Peter et al. | 2020
- 11
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Classification vs Deep Learning in Cancer Degree on Limited Histopathology DatasetsFurtado, Pedro et al. | 2020
- 12
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Biobanks and Biobank-Based Artificial Intelligence (AI) Implementation Through an International LensKozlakidis, Zisis et al. | 2020
- 13
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HistoMapr™: An Explainable AI (xAI) Platform for Computational Pathology SolutionsTosun, Akif Burak / Pullara, Filippo / Becich, Michael J. / Taylor, D. Lansing / Chennubhotla, S. Chakra / Fine, Jeffrey L. et al. | 2020
- 14
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Extension of the Identity Management System Mainzelliste to Reduce Runtimes for Patient Registration in Large DatasetsZerbe, Norman / Hampf, Christopher / Hufnagl, Peter et al. | 2020
- 15
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Digital Image Analysis in Pathology Using DNA Stain: Contributions in Cancer Diagnostics and Development of Prognostic and Theranostic BiomarkersEl Hallani, Soufiane / MacAulay, Calum / Guillaud, Martial et al. | 2020
- 16
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Assessment and Comparison of Colour Fidelity of Whole Slide Imaging ScannersZerbe, Norman / Alekseychuk, Alexander / Hufnagl, Peter et al. | 2020
- 17
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Deep Learning Methods for Mitosis Detection in Breast Cancer Histopathological Images: A Comprehensive ReviewDif, Nassima / Elberrichi, Zakaria et al. | 2020
- 18
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Developments in AI and Machine Learning for NeuroimagingO’Sullivan, Shane / Jeanquartier, Fleur / Jean-Quartier, Claire / Holzinger, Andreas / Shiebler, Dan / Moon, Pradip / Angione, Claudio et al. | 2020
- 19
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Fuzzy Image Processing and Deep Learning for Microaneurysms DetectionRahim, Sarni Suhaila / Palade, Vasile / Almakky, Ibrahim / Holzinger, Andreas et al. | 2020