About the Book:
Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular.
In Artificial Intelligence and Deep Learning in Pathology, with a team of experts, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience.
Table of Contents
The evolution of machine learning: past, present, and futureThe basics of machine learning: strategies and techniquesOverview of advanced neural network architecturesComplexity in the use of artificial intelligence in anatomic pathologyDealing with data: strategies of preprocessing dataDigital pathology as a platform for primary diagnosis and augmentation via deep learningApplications of artificial intelligence for image enhancement in pathology Precision medicine in digital pathology via image analysis and machine learningArtificial intelligence methods for predictive image-based grading of human cancersArtificial intelligence and the interplay between tumor and immunityOverview of the role of artificial intelligence in pathology: the computer as a pathology digital assistant
