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Artificial Intelligence and Machine Learning for Digital Pathology - State-of-the-Art and Future Challenges (Paperback, 1st ed. 2020) Loot Price: R2,408
Discovery Miles 24 080
Artificial Intelligence and Machine Learning for Digital Pathology - State-of-the-Art and Future Challenges (Paperback, 1st ed....

Artificial Intelligence and Machine Learning for Digital Pathology - State-of-the-Art and Future Challenges (Paperback, 1st ed. 2020)

Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Muller

Series: Lecture Notes in Computer Science, 12090

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Loot Price R2,408 Discovery Miles 24 080 | Repayment Terms: R226 pm x 12*

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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.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Lecture Notes in Computer Science, 12090
Release date: June 2020
First published: 2020
Editors: Andreas Holzinger • Randy Goebel • Michael Mengel • Heimo Muller
Dimensions: 235 x 155 x 28mm (L x W x T)
Format: Paperback
Pages: 341
Edition: 1st ed. 2020
ISBN-13: 978-3-03-050401-4
Categories: Books > Medicine > Other branches of medicine > Pathology > Gross pathology
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-03-050401-8
Barcode: 9783030504014

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