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Paperback. Condition: new. Paperback. The integration of large language models (LLMs) and generative artificial intelligence (AI) in health care holds the potential to transform the practice of medicine, the work and experiences of health care providers, and the health and well-being of patients. Generative AI can support clinical decision making and streamline workflows, promote patients and their support networks' engagement in care processes, and support clinical research. However, successful and ethical implementation of generative AI requires careful consideration of the associated risks, particularly those concerning data privacy, bias, transparency, and infrastructure limitations. Generative Artificial Intelligence in Health and Medicine: Opportunities and Responsibilities for Transformative Innovation explores the transformative potential of generative AI in health care, with a focus on its applications in clinical decision making, administrative efficiency, and patient engagement. The integration of large language models (LLMs) and generative artificial intelligence (AI) in health care holds the potential to transform the practice of medicine, the work and experiences of health care providers, and the health and well-being of patients. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Condition: new. Paperback. The integration of large language models (LLMs) and generative artificial intelligence (AI) in health care holds the potential to transform the practice of medicine, the work and experiences of health care providers, and the health and well-being of patients. Generative AI can support clinical decision making and streamline workflows, promote patients and their support networks' engagement in care processes, and support clinical research. However, successful and ethical implementation of generative AI requires careful consideration of the associated risks, particularly those concerning data privacy, bias, transparency, and infrastructure limitations. Generative Artificial Intelligence in Health and Medicine: Opportunities and Responsibilities for Transformative Innovation explores the transformative potential of generative AI in health care, with a focus on its applications in clinical decision making, administrative efficiency, and patient engagement. The integration of large language models (LLMs) and generative artificial intelligence (AI) in health care holds the potential to transform the practice of medicine, the work and experiences of health care providers, and the health and well-being of patients. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Integrative and translational methodologies and frameworks have transformed modern biomedical research and the delivery of clinical care. This shift has been manifested in a number of ways, including the rapid growth and increasing availability of high-throughput bio-molecular instrumentation and analysis platforms, innovative clinical research programs intended to accelerate knowledge translation, and initial efforts to deliver personalized healthcare informed by the genomic profiles of patients. A common theme of reports and publications concerned with such transformative changes in the biomedical and healthcare domains is concerned with the challenges and opportunities related to the collection, management, integration, analysis, and dissemination of large-scale, heterogeneous biomedical data sets. In particular, the absence of well-established and adopted theoretical and practical frameworks intended to address such needs is a major impediment to the realization of translational and knowledge-driven healthcare, in which the best possible scientific evidence is used to inform the care of every patient. In this vacuum, the development of integrative clinical or translational research paradigms is significantly limited by the propagation of both data and expertise silos. This book details for the first time the current state of this extremely potent area of healthcare innovation and policy and defines the interaction between clinical/translational science and biomedical informatics.
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Taschenbuch. Condition: Neu. Translational Informatics | Realizing the Promise of Knowledge-Driven Healthcare | Philip R. O. Payne (u. a.) | Taschenbuch | Health Informatics | ix | Englisch | 2016 | Springer | EAN 9781447172208 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Integrative and translational methodologies and frameworks have transformed modern biomedical research and the delivery of clinical care. This shift has been manifested in a number of ways, including the rapid growth and increasing availability of high-throughput bio-molecular instrumentation and analysis platforms, innovative clinical research programs intended to accelerate knowledge translation, and initial efforts to deliver personalized healthcare informed by the genomic profiles of patients. A common theme of reports and publications concerned with such transformative changes in the biomedical and healthcare domains is concerned with the challenges and opportunities related to the collection, management, integration, analysis, and dissemination of large-scale, heterogeneous biomedical data sets. In particular, the absence of well-established and adopted theoretical and practical frameworks intended to address such needs is a major impediment to the realization of translational and knowledge-driven healthcare, in which the best possible scientific evidence is used to inform the care of every patient. In this vacuum, the development of integrative clinical or translational research paradigms is significantly limited by the propagation of both data and expertise silos. This book details for the first time the current state of this extremely potent area of healthcare innovation and policy and defines the interaction between clinical/translational science and biomedical informatics.