Verlag: Würzburg, 1988
Anbieter: Wissenschaftliches Antiquariat Köln Dr. Sebastian Peters UG, Köln, Deutschland
Zustand: gut. 96 S. : graph. Darst. ; 21 cm, Rand mit Läsur. Sprache: Deutsch.
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In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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In den WarenkorbZustand: New. pp. 341.
Sprache: Deutsch
Verlag: Trier, WVT, 2003
Anbieter: Antiquariat + Verlag Klaus Breinlich, Frankfurt am Main, Deutschland
Verbandsmitglied: BOEV
Gr.-8vo. XIV, 557 S. Originaler Verlagskarton. Verlagsfrischer Zustand! (Proceedings of the Conference of the German Association of University Teachers of English, 24).
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In den WarenkorbPaperback. Zustand: Brand New. 356 pages. 9.25x6.10x0.94 inches. In Stock.
Taschenbuch. Zustand: Neu. Artificial Intelligence and Machine Learning for Digital Pathology | State-of-the-Art and Future Challenges | Andreas Holzinger (u. a.) | Taschenbuch | xii | Englisch | 2020 | Springer | EAN 9783030504014 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer International Publishing, Springer Nature Switzerland Jun 2020, 2020
ISBN 10: 3030504018 ISBN 13: 9783030504014
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -Data 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 356 pp. Englisch.
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data 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.
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In den WarenkorbHardcover. Zustand: Brand New. German language. 10.31x7.52x0.79 inches. In Stock.