Overview
- 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 broad applications of Artificial Intelligence in digital pathology
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12090)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
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Table of contents (19 chapters)
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Front Matter
Keywords
- artificial intelligence
- bioinformatics
- computer science
- computer systems
- computer vision
- databases
- deep learning
- education
- engineering
- expert systems
- image analysis
- image processing
- information systems
- information technology
- intelligent systems
- learning
- machine learning
- mathematics
- medical images
- neural networks
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Artificial Intelligence and Machine Learning for Digital Pathology
Book Subtitle: State-of-the-Art and Future Challenges
Editors: Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-50402-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-50401-4Published: 21 June 2020
eBook ISBN: 978-3-030-50402-1Published: 24 June 2020
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XII, 341
Number of Illustrations: 11 b/w illustrations, 84 illustrations in colour
Topics: Artificial Intelligence, Computing Milieux, Database Management, Computer Applications, Systems and Data Security, Image Processing and Computer Vision