Interpretable Three Way Decision With Hesitant Risk Information And Its Healthcare Application
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Interpretable Three-Way Decision with Hesitant Risk Information and Its Healthcare Application
As a new interpretable model, three-way decision has also received academic attention in machine learning. With respect to different hesitant fuzzy information, this book deeply discusses the deduction process of decision rules of three-way decision and generates interpretable knowledge with the risk semantics. It further explores the applications of three-way decision to support healthcare management. This book is used as a reference for engineers, technicians, and researchers who are working in the fields of management science, operation management, computer science, information management, fuzzy mathematics, business intelligence, and other fields. It also serves as a textbook for postgraduate and senior undergraduate students of the relevant professional institutions of higher learning.
Explainable Artificial Intelligence in the Healthcare Industry
Discover the essential insights and practical applications of explainable AI in healthcare that will empower professionals and enhance patient trust with Explainable AI in the Healthcare Industry, a must-have resource. Explainable AI (XAI) has significant implications for the healthcare industry, where trust, accountability, and interpretability are crucial factors for the adoption of artificial intelligence. XAI techniques in healthcare aim to provide clear and understandable explanations for AI-driven decisions, helping healthcare professionals, patients, and regulatory bodies to better comprehend and trust the AI models’ outputs. Explainable AI in the Healthcare Industry presents a comprehensive exploration of the critical role of explainable AI in revolutionizing the healthcare industry. With the rapid integration of AI-driven solutions in medical practice, understanding how these models arrive at their decisions is of paramount importance. The book delves into the principles, methodologies, and practical applications of XAI techniques specifically tailored for healthcare settings.
Can AI Be Your Family Doctor? A New Era in Personalized Healthcare
As we stand on the precipice of a new era in healthcare, the integration of artificial intelligence (AI) into medical practice invites both excitement and trepidation. The question at the heart of this book, Can AI Be Your Family Doctor? arises from a world increasingly influenced by technological advancements. Family medicine, traditionally anchored in the principles of compassion, continuity, and comprehensive care, is being reshaped by the capabilities of AI to analyze vast amounts of data, enhance diagnostic accuracy, and personalize treatment plans. In recent years, we have witnessed rapid developments in AI applications across various sectors, and healthcare is no exception. The emergence of AI-driven tools is promising, offering solutions to some of the most pressing challenges in medicine, such as patient management, early disease detection, and equitable access to care. However, these advancements also prompt essential discussions about ethics, the preservation of human touch in medicine, and the future roles of healthcare professionals. This book endeavors to explore the multifaceted relationship between AI and family medicine. It does not seek to replace the invaluable human element of patient care but rather to investigate how AI can complement and enhance the work of family doctors. Through comprehensive research, real-world case studies, and insights from healthcare experts, we will uncover the potential of AI as a partner in the healthcare journey, providing tools that empower patients and practitioners alike. As we navigate this transformative landscape, it is crucial to engage in thoughtful dialogue about the implications of AI in healthcare. Our aim is not only to inform but also to inspire readers to consider the future possibilities of family medicine—one where AI acts as an ally, fostering a more informed and healthier society. I invite you, the reader, to join me on this journey of discovery. Together, we will explore the capabilities and limitations of AI in healthcare, examine ethical considerations, and envision a future where technology and human empathy coexist harmoniously for the betterment of patient care.