Abhishek Kumar,Ashutosh Kumar Dubey,Sreenatha G. Anavatti,Pramod Singh Rathore
Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
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- More about Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
The book "Machine Learning in Healthcare Informatics: Methods, Paradigms, and Applications" is a comprehensive guide that explores machine learning techniques and their applications in healthcare informatics. It offers a diverse range of methods and paradigms to empower multi-disciplinary and multi-institutional research, provides a snapshot of current and emerging healthcare informatics paradigms, and highlights the complexity of the field through case studies.
Format: Hardback
Length: 224 pages
Publication date: 10 March 2022
Publisher: Taylor & Francis Ltd
Delivers a comprehensive and up-to-date overview of machine learning in healthcare informatics
The book presents a diverse range of techniques aimed at enhancing and empowering multi-disciplinary and multi-institutional machine learning research. It serves as a comprehensive compendium of current and emerging machine learning paradigms specifically tailored for healthcare informatics. Through the use of case studies, the book explores the richness and complexity of the field, highlighting the diversity of approaches and methodologies employed.
The book provides a panoramic view of data and machine learning techniques, offering valuable insights and opportunities for novel discoveries. It delves into the theoretical foundations and practical applications of machine learning in healthcare, covering a wide range of topics such as medical image analysis, natural language processing, and predictive modeling.
In addition, the book includes a guided tour of machine learning algorithms, architecture design, and applications, showcasing their practical implications in interdisciplinary challenges. This comprehensive and up-to-date overview of machine learning in healthcare informatics is designed to assist researchers, practitioners, and students in understanding and leveraging the power of machine learning to improve healthcare outcomes and advance medical research.
Dimension: 234 x 156 (mm)
ISBN-13: 9780367676339
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