Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
“Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics” by Abhishek Kumar, published by Taylor & Francis Group in 2022, is a comprehensive resource that delves into the evolving landscape of machine learning within healthcare informatics. Spanning 224 pages, this edition presents a detailed overview of current and emerging paradigms, methodologies, and applications in the field, highlighting the diversity and complexity of machine learning techniques.
Readers will find a variety of techniques aimed at enhancing interdisciplinary research in healthcare data analytics. The book includes numerous case studies and offers insights into machine learning algorithms, architecture design, and the challenges faced in practical applications. It serves as a valuable reference for research scholars and students engaged in critical condition analysis and computational models, providing a guided exploration of the intersection between artificial intelligence and healthcare.
Official synopsis Publisher
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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