Introduction to artificial intelligence / Michail E. Klontzas, Salvatore Claudio Fanni, Emanuele Neri, editors.
Klontzas, Michail E. editor.; Fanni, Salvatore Claudio, editor.; Neri, E. (Emanuele), editor.
2023
RC78.7.D53
Available Online

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Title Introduction to artificial intelligence / Michail E. Klontzas, Salvatore Claudio Fanni, Emanuele Neri, editors.
ISBN 9783031259289 (electronic bk.)
3031259289 (electronic bk.)
3031259270
9783031259272
DOI https://doi.org/10.1007/978-3-031-25928-9
Published Cham, Switzerland : Springer, 2023.
Language English
Description 1 online resource (130 pages) : illustrations (black and white, and color).
Other Standard Identifiers 10.1007/978-3-031-25928-9 doi
Call Number RC78.7.D53
Dewey Decimal Classification 616.0754028563
Summary This book aims to provide physicians and scientists with the basics of Artificial Intelligence (AI) with a special focus on medical imaging. The contents of the book provide an introduction to the main topics of artificial intelligence currently applied on medical image analysis. The book starts with a chapter explaining the basic terms used in artificial intelligence for novice readers and embarks on a series of chapters each one of which provides the basics on one AI-related topic. The second chapter presents the programming languages and available automated tools that enable the development of AI applications for medical imaging. The third chapter endeavours to analyse the main traditional machine learning techniques, explaining algorithms such as random forests, support vector machines as well as basic neural networks. The applications of those machines on the analysis of radiomics data is expanded in the fourth chapter to allow the understanding of algorithms used to build classifiers for the diagnosis of disease processes with the use of radiomics. Chapter five provides the basics of natural language processing which has revolutionized the analysis of complex radiological reports and chapter six affords a succinct introduction to convolutional neural networks which have revolutionized medical image analysis enabling automated image-based diagnosis, image enhancement (e.g. denoising), protocolling etc. The penultimate chapter provides an introduction to data preprocessing for use in the aforementioned artificial intelligence applications. The book concludes with a chapter demonstrating AI-based tools already in radiological practice while providing an insight about the foreseeable future. It will be a valuable resource for radiologists, computer scientists and postgraduate students working on medical image analysis.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Klontzas, Michail E. editor.
Fanni, Salvatore Claudio, editor.
Neri, E. (Emanuele), editor.
Series Imaging informatics for healthcare professionals
Available in Other Form INTRODUCTION TO ARTIFICIAL INTELLIGENCE.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
What is Artificial Intelligence: History and Basic Definitions
Programming Languages and Tools Used for AI Applications
Introduction to Traditional Machine Learning
Machine Learning Methods for Radiomics Analysis
Natural Language Processing (NLP)
Deep Learning
Data Preparation for AI Purposes
Current Applications of AI in Medical Imaging. .

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