Healthcare Solutions Using Machine Learning and Informatics

Focuses on fundamental concepts of gathering, processing, analyzing the dataset from rich healthcare and biomedical sources. Covers interdisciplinary techniques such as data science, deep learning, statistics, big data analytics, smart devices, computer vision and IoT.

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Healthcare Solutions Using Machine Learning and Informatics covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artificial intelligence, machine learning, and intelligent IoT-based solutions for medical image analysis, medical big-data processing, and disease predictions. Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence.

The wide variety of topics covered include:



Artificial Intelligence in healthcare
Machine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19
Big data analytics solutions for healthcare data processing
Reliable biomedical applications using AI models
Intelligent IoT in healthcare

The book explains fundamental concepts as well as the advanced use cases, illustrating how to apply emerging technologies such as machine learning, AI models, and data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. Chapters contributed by noted academicians and professionals examine various solutions, frameworks, applications, case studies, and best practices in the healthcare domain.