How Artificial Intelligence Is Transforming Healthcare It Applications In Diagnostics Treatment Planning And Patient Monitoring

How Artificial Intelligence is Transforming Healthcare IT: Applications in Diagnostics, Treatment Planning, and Patient Monitoring

Transforming Healthcare with Artificial Intelligence

This book presents the groundbreaking ways artificial intelligence (AI) is revolutionizing the healthcare industry and delves into how AI technologies are enhancing patient care, improving diagnostic accuracy, and streamlining healthcare operations. With real-world examples of how AI is being used in hospitals, clinics, and research institutions around the world as well as insights from leading experts who provide readers with access to cutting-edge knowledge and diverse perspectives on the future of medicine, the book provides a comprehensive overview of the innovations driving the future of medicine. Healthcare is facing big challenges including the growing demand for medical services, the need for more accurate diagnoses, and the pressure to reduce costs. AI can help solve these problems by making healthcare more efficient, precise, and accessible to everyone. Appropriate for healthcare professionals, technology enthusiasts, or simply curious readers about the future of healthcare, this book offers a clear and engaging look at how AI is reshaping the medical landscape for the better. Specifically, the book covers various aspects of AI in healthcare, including diagnostics, treatment planning, patient monitoring, hospital management, and public health. In addition, the book presents the ethical, legal, and societal implications, providing a well-rounded discussion that considers both the opportunities and challenges of AI in healthcare.

The Artificial Intelligence and Machine Learning Blueprint: Foundations, Frameworks, and Real-World Applications

In the current era of data-centric transformation, Artificial Intelligence (AI) and Machine Learning (ML) are influencing organizational strategies and operations. The AI and Machine Learning Blueprint serves as a guide connecting academic concepts with industry applications. It is intended for both students seeking basic knowledge and professionals interested in deploying scalable AI systems. The book covers core mathematical principles relevant to AI, including linear algebra, probability, statistics, and optimization, and provides an overview of classical machine learning algorithms, neural networks, and reinforcement learning. Concepts are illustrated with practical examples, Python code, and case studies from sectors such as healthcare, finance, cybersecurity, natural language processing, and computer vision. Operational considerations are also addressed, with chapters on MLOps, model deployment, explainable AI (XAI), and ethics. The text concludes with information on emerging topics including generative AI, federated learning, and artificial general intelligence (AGI). With a blend of theoretical depth and practical relevance, this book is an essential blueprint for mastering AI and ML in today’s intelligent systems landscape.