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Digital Pathology: Implementation in Clinical Practice with AI applications

Autor Meera Hameed, Matthew G Hanna
en Limba Engleză Paperback – 27 noi 2024
Digital Pathology: Implementation in Clinical Practice with AI Applications covers digital pathology applications in a clinical pathology laboratory setting, providing guidance and various tools for practical implementation. This comprehensive and detailed description of nuts and bolts of digital pathology implementation is unique and comes from the experience of high throughput scanning from a large surgical pathology laboratory. This is a valuable reference to prepare the end users not only about thoughtful launch of digital pathology but also to prepare for the future use of AI mediated decision support tools as the field advances. This book covers the entire range of this topic and can be used as a practical reference for individuals that wish to be part of the evolution of diagnostic pathology. Sections include pre-analytic, analytic, and post-analytic processes, encompassing hardware, software, space, staffing, quality control, laboratory information system applications, clinical validation, use cases and future applications, including computer assisted diagnosis and decision support tools.


  • Provides detailed aspects of the implementation of digital pathology in the clinical laboratory, including machine learning/artificial intelligence tools
  • Presents examples of how digital imaging and AI are drivers in research and development in radiology, with parallels to situations in pathology
  • Includes best practices and guidelines that can be practically applied by pathologists and data scientists
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Specificații

ISBN-13: 9780443138096
ISBN-10: 0443138095
Pagini: 352
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE

Cuprins

1. Basics of Digital Pathology
2. The 5 S’s for Success (Sponsorship, Staffing, Storage, Space, Scanners)
3. Pre-analytics
4. Analytic and post-analytic factors
5. Use cases in Anatomic Pathology
6. Use Cases in Clinical Pathology
7. The Pathologist’s Portal: optimal integration of digital data
8. Regulatory aspects of digital pathology
9. The basics of Machine Learning and AI
10. Machine Learning and AI applications
11. Integration of Diagnostic Imaging in Radiology and Pathology