This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.