Items related to Artificial Intelligence and Machine Learning for Digital...
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges (Lecture Notes in Artificial Intelligence) - Softcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About this title" may belong to another edition of this title.
Search results for Artificial Intelligence and Machine Learning for Digital...
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology. State-of-the-Art and Future Challenges.
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Seller rating 5 out of 5 stars
XII, 339 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Lecture Notes in Artificial Intelligence ; 12090. Sprache: Englisch. Seller Inventory # 7019BB
Quantity: 1 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology, State-of-the-Art and Future Challenges
Seller: Basi6 International, Irving, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEJUNE24-13458
Quantity: 1 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges (Lecture Notes in Computer Science)
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. pp. 341. Seller Inventory # 26379018958
Quantity: 1 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges (Lecture Notes in Computer Science)
Seller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. pp. 341. Seller Inventory # 383836433
Quantity: 1 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges (Lecture Notes in Computer Science)
Seller: Biblios, Frankfurt am main, HESSE, Germany
Seller rating 5 out of 5 stars
Condition: New. pp. 341. Seller Inventory # 18379018948
Quantity: 1 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges (Lecture Notes in Artificial Intelligence)
Seller: ALLBOOKS1, Direk, SA, Australia
Seller rating 5 out of 5 stars
Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address. Seller Inventory # SHUB13458
Quantity: 1 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges (Lecture Notes in Artificial Intelligence)
Seller: Best Price, Torrance, CA, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. SUPER FAST SHIPPING. Seller Inventory # 9783030504014
Quantity: 3 available
Stock Image
Artificial Intelligence and Machine Learning for Digital Pathology (Paperback)
Published by
Springer Nature Switzerland AG, Cham, 2020
ISBN 10: 3030504018
ISBN 13: 9783030504014
New
Paperback
First Edition
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783030504014
Quantity: 1 available
Seller Image
Artificial Intelligence and Machine Learning for Digital Pathology
Published by
Springer International Publishing, Springer Nature Switzerland Jun 2020, 2020
ISBN 10: 3030504018
ISBN 13: 9783030504014
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 356 pp. Englisch. Seller Inventory # 9783030504014
Quantity: 2 available
Seller Image
Artificial Intelligence and Machine Learning for Digital Pathology
Published by
Springer International Publishing, 2020
ISBN 10: 3030504018
ISBN 13: 9783030504014
New
Softcover
Seller: moluna, Greven, Germany
Seller rating 4 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Digital pathology is a disruptive innovation that will markedly change health care in the next few years Biobanks play a central role providing large collections of high-quality well-annotated samples and data Future. Seller Inventory # 385700374
Quantity: Over 20 available