Deep Learning and Other Soft Computing Techniques : Biomedical and Related Applications

Vladik Kreinovich

ISBN 10: 3031294491 / ISBN 13: 9783031294495

Published by Springer Nature Switzerland, 2024

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the use of artificial intelligence (AI) and computationalintelligence (CI) in medical and related applications. Applications includeall aspects of medicine: from diagnostics (including analysis of medicalimages and medical data) to therapeutics (including drug designand radiotherapy) to epidemic- and pandemic-related public health policies.Corresponding techniques include machine learning (especially deep learning),techniques for processing expert knowledge (e.g., fuzzy techniques), andadvanced techniques of applied mathematics (such as innovative probabilisticand graph-based techniques).The book also shows that these techniques can be used in many otherapplications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI andCI methods and their biomedical (and related) applications-and to furtherdevelop thisimportant research direction.

Seller Inventory # 9783031294495

Bibliographic Details

• Title: Deep Learning and Other Soft Computing Techniques : Biomedical and Related Applications
• Publisher: Springer Nature Switzerland
• Publication Date: 2024
• Language: English
• ISBN 10: 3031294491
• ISBN 13: 9783031294495
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

This book focuses on the use of artificial intelligence (AI) and computational intelligence (CI) in medical and related applications. Applications include all aspects of medicine: from diagnostics (including analysis of medical images and medical data) to therapeutics (including drug design and radiotherapy) to epidemic- and pandemic-related public health policies.

Corresponding techniques include machine learning (especially deep learning), techniques for processing expert knowledge (e.g., fuzzy techniques), and advanced techniques of applied mathematics (such as innovative probabilistic and graph-based techniques).

The book also shows that these techniques can be used in many other applications areas, such as finance, transportation, physics.

This book helps practitioners and researchers to learn more about AI and CI methods and their biomedical (and related) applications―and to further develop thisimportant research direction.