Overview
- Provides an overview of artificial intelligence techniques, specifically machine learning and deep learning techniques, for tracking and preventing diseases
- Is an introduction to “Tracking and Preventing Diseases with Artificial Intelligence”
- Present in the first chapters the theory and state-of-the-art techniques used in a simple way
- Discusses advanced techniques, current trends, and open challenges
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 206)
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Table of contents (11 chapters)
Keywords
About this book
This book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions.
The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides itsuse in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases.
Editors and Affiliations
Bibliographic Information
Book Title: Tracking and Preventing Diseases with Artificial Intelligence
Editors: Mayuri Mehta, Philippe Fournier-Viger, Maulika Patel, Jerry Chun-Wei Lin
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-030-76732-7
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-76731-0Published: 15 July 2021
Softcover ISBN: 978-3-030-76734-1Published: 16 July 2022
eBook ISBN: 978-3-030-76732-7Published: 14 July 2021
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XX, 252
Number of Illustrations: 31 b/w illustrations, 86 illustrations in colour
Topics: Computational Intelligence, Biomedical Engineering and Bioengineering, Artificial Intelligence