Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
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Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics

 EPUB
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ISBN-13:
9781000539981
Veröffentl:
2022
Einband:
EPUB
Seiten:
240
Autor:
Sreenatha G. Anavatti
Serie:
Innovations in Big Data and Machine Learning
eBook Typ:
EPUB
eBook Format:
EPUB
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Deutsch
Beschreibung:

In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.
In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques, providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design and interdisciplinary challenges. This book is useful for research scholars and students involved in critical condition analysis and computation models.

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