000 | 05445nam a22006615i 4500 | ||
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001 | 978-3-030-50402-1 | ||
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007 | cr nn 008mamaa | ||
008 | 200620s2020 sz | s |||| 0|eng d | ||
020 |
_a9783030504021 _9978-3-030-50402-1 |
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024 | 7 |
_a10.1007/978-3-030-50402-1 _2doi |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
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_aArtificial Intelligence and Machine Learning for Digital Pathology _h[electronic resource] : _bState-of-the-Art and Future Challenges / _cedited by Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller. |
250 | _a1st ed. 2020. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
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300 |
_aXII, 341 p. 95 illus., 84 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v12090 |
|
505 | 0 | _aExpectations of Artificial Intelligence for Pathology -- Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images -- Supporting the Donation of Health Records to Biobanks for Medical Research -- Survey of XAI in Digital Pathology -- Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for Biobanks -- Black Box Nature of Deep Learning for Digital Pathology: Beyond Quantitative to Qualitative Algorithmic Performances -- Towards a Better Understanding of the Workflows: Modeling Pathology Processes in View of Future AI Integration -- OBDEX - Open Block Data Exchange System -- Image Processing and Machine Learning Techniques for Diabetic Retinopathy Detection: A Review -- Higher Education Teaching Material on Machine Learning in the Domain of Digital Pathology -- Classification vs Deep Learning in Cancer Degree on Limited Histopathology Datasets -- Biobanks and Biobank-Based Artificial Intelligence (AI) Implementation Throughan International Lens -- HistoMapr: An Explainable AI (xAI) Platform for Computational Pathology Solutions -- Extension of the Identity Management System Mainzelliste to Reduce Runtimes for Patient Registration in Large Datasets -- Digital Image Analysis in Pathology Using DNA Stain: Contributions in Cancer Diagnostics and Development of Prognostic and Theranostic Biomarkers -- Assessment and Comparison of Colour Fidelity of Whole slide imaging scanners -- Deep Learning Methods for Mitosis Detection in Breast Cancer Histopathological Images: a Comprehensive Review -- Developments in AI and Machine Learning for Neuroimaging. | |
520 | _aData driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ''fit-for-purpose'' samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions. | ||
650 | 0 |
_aArtificial intelligence. _93407 |
|
650 | 0 |
_aComputers. _98172 |
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650 | 0 |
_aDatabase management. _93157 |
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650 | 0 |
_aSocial sciences _xData processing. _983360 |
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650 | 0 |
_aData protection. _97245 |
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650 | 0 |
_aComputer vision. _9111688 |
|
650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aComputing Milieux. _955441 |
650 | 2 | 4 |
_aDatabase Management. _93157 |
650 | 2 | 4 |
_aComputer Application in Social and Behavioral Sciences. _931815 |
650 | 2 | 4 |
_aData and Information Security. _931990 |
650 | 2 | 4 |
_aComputer Vision. _9111689 |
700 | 1 |
_aHolzinger, Andreas. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9111690 |
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700 | 1 |
_aGoebel, Randy. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9111691 |
|
700 | 1 |
_aMengel, Michael. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9111692 |
|
700 | 1 |
_aMüller, Heimo. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9111693 |
|
710 | 2 |
_aSpringerLink (Online service) _9111694 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030504014 |
776 | 0 | 8 |
_iPrinted edition: _z9783030504038 |
830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v12090 _9111695 |
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856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-50402-1 |
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