Artificial intelligence applications medicine (73 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware - Fundamentals of Artificial Intelligence in Medicine is a comprehensive medical textbook for students, clinicians, healthcare educators, informatics professionals, and medical leaders who want to understand how artificial intelligence is reshaping modern healthcare.Written with a clear academic voice, this book explains the foundations of AI in medicine, including machine learning, deep learning, clinical decision support, medical imaging, natural language processing, digital diagnostics, genomics, therapeutics, ethics, privacy, safety, validation, bias, workflow integration, and responsible implementation.The book connects technical concepts to real clinical practice, showing how AI can support diagnosis, risk prediction, documentation, imaging interpretation, personalized treatment, patient safety, and healthcare system improvement. Rather than treating AI as a replacement for clinicians, it presents artificial intelligence as a clinical tool that must be understood, validated, governed, and safely integrated into patient care.Inside, readers will find practical explanations of medical data sources, algorithmic reasoning, clinical AI workflows, model evaluation, bias reduction, human factors, governance, and future directions in responsible medical intelligence. Each chapter is structured to support deep learning, practical application, and professional understanding.Ideal for medical students, nursing students, clinicians, healthcare administrators, digital health professionals, biomedical science learners, and anyone preparing for the future of AI-enabled medicine, this book provides a strong foundation for understanding both the promise and the responsibilities of artificial intelligence in healthcare.…

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Zustand: Normal. North-Holland. Amsterdam, 1978 24 x 16,5 cm., 195 pag. Tapa blanda; buen estado de conservacion. REVISTAS Y PUBLICACIONES . Ejemplares disponibles: 1 Normal.

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Taschenbuch. Zustand: Neu. Artificial Intelligence in Medicine | Applications, Limitations and Future Directions | Manda Raz (u. a.) | Taschenbuch | viii | Englisch | 2023 | Springer | EAN 9789811912252 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 268 | Sprache: Englisch | Produktart: Bücher | This book identifies Artificial Intelligence (AI) as a growing field that is being incorporated into many aspects of human life, including healthcare practice and delivery. The precision, automation, and potential of AI brings multiple benefits to the way disease is diagnosed, investigated and treated. Currently, there is a lack of any appreciable understanding of AI and this book provides detailed understandings, which include; foundational concepts, current applications, future challenges amongst most healthcare practitioners. The book is divided into four sections: basic concepts, current applications, limitations and future directions. Each section is comprised of chapters written by expert academics, researchers and practitioners at the intersection between AI and medicine. The purpose of the book is to promote AI literacy as an important component of modern medical practice. This book is suited for all readers as it requires no previous knowledge, it walks non-technical clinicians through the complex ideas and concepts in an easy to understand manner. …

Buch. Zustand: Neu. Neuware - The rapid advancements in artificial intelligence technology have paved the way for the use of machine learning applications in health care. These applications address existing challenges in the emergency department such as triage and disposition, early detection of conditions and outcomes, emergency department operations, and therapeutic interventions. Artificial intelligence can be used in three ways in the context of emergency and critical care. The first one is to build risk stratification prediction models in critical care. The second use of AI involves utilizing unsupervised machine learning techniques to divide the varied population into homogeneous subgroups. The third use of AI is for reinforcement learning algorithms to prescribe treatment regimens in a sequential way. The dynamic treatment regime (DTR) model uses reinforcement learning to estimate a set of decision rules, one for each step of intervention. It specifies how to tailor treatments to patients considering their treatment and covariate histories. DTR lowers model complexity and is considered more appropriate for medical epidemiology. This book is a vital tool for all researching or studying the role of AI in emergency medicine. It aims to equip students and experts with the advanced topics and upcoming concepts in this subject.…

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