Artificial Intelligence and Deep Learning in Pathology - 1st Edition - ISBN: 9780323675383

Artificial Intelligence and Deep Learning in Pathology

1st Edition

Editors: Stanley Cohen
Paperback ISBN: 9780323675383
Imprint: Elsevier
Published Date: 1st June 2020
Page Count: 250

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


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

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


No. of pages:
© Elsevier 2021
1st June 2020
Paperback ISBN:

About the Editor

Stanley Cohen

Affiliations and Expertise

Emeritus Founding Director, Center for Biophysical Pathology, Rutgers-NJMS; Adjunct Professor of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois; Perelman School of Medicine at the University of Pennsylvania, Sidney Kimmell Medical College - Thomas Jefferson University, Philadelphia, Pennsylvania