Publisher's Synopsis
As the demand for advanced technologies to revolutionize patient care intensifies, the medical industry faces a pressing need to confront challenges hindering the assimilation of AI-enhanced healthcare systems. Issues such as data interoperability, ethical considerations, and the translation of AI advancements into practical clinical applications pose formidable hurdles that demand immediate attention. It is within this context of challenges and opportunities that the book, Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems promises to pave the way for a transformative era in healthcare. The book serves as a comprehensive guide for academic scholars, researchers, and healthcare professionals navigating the dynamic landscape of data-driven, AI-enhanced healthcare. By showcasing the latest advancements, the book empowers its readers to not only comprehend the existing frontiers in data sciences and healthcare technologies but also to actively contribute to overcoming obstacles. Through detailed case studies and practical guidance, the publication equips its audience with the skills necessary to implement AI in various clinical settings. This book targets a diverse audience including data scientists, software engineers, clinicians, researchers, academics, and students. By fostering collaboration and knowledge exchange, the book emerges as a driving force for collective progress in the integration of artificial intelligence and new technologies into healthcare. Policymakers, too, stand to gain valuable insights, enabling them to update technical standards, clinical guidelines, and regulations, thereby optimizing the distribution of medical resources in the realm of data-driven healthcare. From quantum-enhanced machine learning to ethical considerations in AI-enhanced data-driven healthcare systems, the book stands as a rallying call for the healthcare community to overcome challenges, propelling us towards a future where artificial intelligence integrates with advanced technologies to redefine healthcare paradigms.
