Artificial intelligence and deep learning in pathology. (2020)

• Record Type: Book
• Further Information: Note: Stanley Cohen.
• Authors: Cohen, Stanley, 1937-
• Contents: Introduction: The Nature of Artificial Intelligence: Machine Learning and Deep Learning in Digital Pathology Before Deep Learning: Statistical Analysis and Signal Processing, Classical Machine Learning (Geometric, Probabilistic, and Tree Methods, the Perceptron) Whole Slide Imaging for 2D and 3D analysis: techniques and standardization Digital Pathology as a Platform for Primary Diagnosis and Augmentation via Deep Learning Introductory Deep Learning: Convolutional Neural Networks for Extraction, Classification and Prediction from images Advanced Neural networks (Reinforcement, Generative and Genetic Models, Variational encoders, Attention and Memory Networks, Deep Belief Networks) AI Methods for Grading Human Cancers Multilabel Classification (CNN-RNN), Prediction, and Risk Analysis Advances in AI for Pathologists: Petascale AI, Data Warehousing and Repositories Progress in Sparsely Supervised & Unsupervised Learning Overview of the Role of AI in Anatomic Pathology: The Computer as Pathology Assistant Summary and Overview: Emerging New Imaging Technologies and The Rise of the Machine: Human vs Computer capabilities
• Publisher Details: Amsterdam : Elsevier
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 616.07028563; Pathology -- Data processing; Artificial intelligence -- Medical applications
• Languages: English
• ISBNs: 9780323675376
• Related ISBNs: 9780323675383
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.