Artificial Intelligence in Pathology

PART I PRINCIPLES
1. The evolution of machine learning
2. Basics of machine learning strategies
3. Overview of advanced neural network architectures
4. Complexity in the use of AI in anatomic pathology
5. Quantum Artificial Intelligence: Things to come
6. Dealing with data: strategies for pre-processing
7. Easing the Burden of Annotation in pathology
8. Digital path as a platform for primary diagnosis and augmentation via a deep learning
9. Challenges in the Development, Deployment, and Regulation of AI in Anatomic Pathology
10. Ethics of AI in Pathology: Current Paradigms and Emerging Issues

PART II APPLICATIONS
11. Image enhancement via AI
12. Artificial Intelligence and Cellular Segmentation in Tissue Microscopy Images
13. Precision medicine in digital pathology
14. Generative Deep Learning in Digital Pathology Workflows
15. Predictive image-based grading of human cancer
16. The interplay between tumor and immunity
17. Machine-based evaluation intra-tumoral heterogeneity and tumor-stromal interface

PART III OVERVIEW
18. The computer as digital pathology assistant
19. Neuromorphic computing, general AI, and the future of pathology

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• Patologia
• Inteligência artificial

Artificial Intelligence; Anatomic Pathology; Quantum Artificial Intelligence; Artificial Intelligence Ethics; Machine Learning; Deep Learning; Neuromorphic Computing; Precision Medicine; Image Annotation; Regulation of Artificial Intelligence