Artificial Intelligence and Machine Learning for Digital Pathology
Andreas Holzinger (Redaktør) Randy Goebel (Redaktør) Michael Mengel (Redaktør) Heimo Müller (Redaktør)
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. Les mer
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.
Detaljer
- Forlag
- Springer Nature Switzerland AG
- Innbinding
- Paperback
- Språk
- Engelsk
- Sider
- 341
- ISBN
- 9783030504014
- Utgivelsesår
- 2020
- Format
- 24 x 16 cm