Introduction

The Digital Transformation of Healthcare: The Impact of AI and Machine Learning examines how AI, Machine Learning, Data Science and digital technologies are reshaping modern healthcare delivery. Across fourteen chapters, it covers AI-driven medical diagnosis, radiological and nuclear medicine imaging, brain abnormality detection via MRI, retinal disease analysis, Alzheimer's detection through EEG, mental state prediction, cardiology and endocrinology monitoring, IoT-enabled smart healthcare, wearables, assistive devices and blockchain-enabled systems for secure patient data management. Throughout, it balances the opportunities and challenges of integrating advanced technologies into clinical practice, with emphasis on patient outcomes, operational efficiency and data-driven decision-making.

Key Features

• - Real-world healthcare case studies across multiple specialties.
• - AI/ML algorithms for medical diagnosis and disease prediction.
• - IoT-based health monitoring and wearable technology frameworks.
• - Blockchain-enabled security solutions for patient data privacy.
• - Multidisciplinary perspectives from healthcare, engineering and data science.

Target Readership :

Researchers, academicians, healthcare professionals, biomedical engineers, data scientists and postgraduate students; secondarily, policymakers, healthcare administrators and technology practitioners.