Marius Fieschi – författare

Health Data Processing: Systemic Approaches focuses on the design of health information systems and touches on the main themes of medical informatics and public health. The book is written for health professionals in practice or training, and is especially useful for decision-makers or future decision-makers in the field of health information systems. Users will find sections on the question of reusing data for other purposes, protection of individual liberties that this data and technologies make more acute, and the irruption of large masses of genetic data and its related problems. This book develops the methodological and conceptual aspects related to these issues.- Proposes a methodology for the development of health information systems for the better use of digital technologies- Illustrates a systemic, transversal, conceptual vision that supports the complex reality of the healthcare world, where the interoperability of agents (professionals and software) is central- Discusses the reuse of resources of data for knowledge improvement, health security and public health

Introduction to Clinical Informatics fills a void in the Computer in Health Care series. With this volume, Patrice Degoulet and Marius Fieschi provide a comprehensive view of medical informatics and carry that concept forward into the realm of clinical informatics. The authors draw upon their experi­ ences as medical school faculty members in France, where informatics has long been integrated into the curriculum and where the French version of this very book has been used, tested, and revised. In intent and content, this volume stands as the companion volume to Introduction to Nursing Informatics, one of the series' best selling titles. For practitioners and students of medicine, pharmacy, and other health profes­ sions, Introduction to Clinical Informatics offers an essential understanding how computing can support patient care, clarifying practical uses and critical issues. Today medical schools in the United States are making informatics a part of their curriculum, with required medical informatics blocks at the onset of training serving as the base for problem-based learning throughout the course of study. In an increasingly networked and computerized environ­ ment, health-care providers are having to alter how they practice. Whether in the office, the clinic, or the hospital, health-care professionals have access to a growing array of capabilities and tools as they deliver care. Learning to use these becomes a top priority, and this volume becomes a valuable resource.

Introduction to Clinical Informatics fills a void in the Computer in Health Care series. With this volume, Patrice Degoulet and Marius Fieschi provide a comprehensive view of medical informatics and carry that concept forward into the realm of clinical informatics. The authors draw upon their experi­ ences as medical school faculty members in France, where informatics has long been integrated into the curriculum and where the French version of this very book has been used, tested, and revised. In intent and content, this volume stands as the companion volume to Introduction to Nursing Informatics, one of the series'' best selling titles. For practitioners and students of medicine, pharmacy, and other health profes­ sions, Introduction to Clinical Informatics offers an essential understanding how computing can support patient care, clarifying practical uses and critical issues. Today medical schools in the United States are making informatics a part of their curriculum, with required medical informatics blocks at the onset of training serving as the base for problem-based learning throughout the course of study. In an increasingly networked and computerized environ­ ment, health-care providers are having to alter how they practice. Whether in the office, the clinic, or the hospital, health-care professionals have access to a growing array of capabilities and tools as they deliver care. Learning to use these becomes a top priority, and this volume becomes a valuable resource.

Introduction to Clinical Informatics fills a void in the Computer in Health Care series. With this volume, Patrice Degoulet and Marius Fieschi provide a comprehensive view of medical informatics and carry that concept forward into the realm of clinical informatics. The authors draw upon their experi­ ences as medical school faculty members in France, where informatics has long been integrated into the curriculum and where the French version of this very book has been used, tested, and revised. In intent and content, this volume stands as the companion volume to Introduction to Nursing Informatics, one of the series' best selling titles. For practitioners and students of medicine, pharmacy, and other health profes­ sions, Introduction to Clinical Informatics offers an essential understanding how computing can support patient care, clarifying practical uses and critical issues. Today medical schools in the United States are making informatics a part of their curriculum, with required medical informatics blocks at the onset of training serving as the base for problem-based learning throughout the course of study. In an increasingly networked and computerized environ­ ment, health-care providers are having to alter how they practice. Whether in the office, the clinic, or the hospital, health-care professionals have access to a growing array of capabilities and tools as they deliver care. Learning to use these becomes a top priority, and this volume becomes a valuable resource.

Health Data Processing: Systemic Approaches focuses on the design of health information systems and touches on the main themes of medical informatics and public health. The book is written for health professionals in practice or training, and is especially useful for decision-makers or future decision-makers in the field of health information systems. Users will find sections on the question of reusing data for other purposes, protection of individual liberties that this data and technologies make more acute, and the irruption of large masses of genetic data and its related problems. This book develops the methodological and conceptual aspects related to these issues.

Proposes a methodology for the development of health information systems for the better use of digital technologies Illustrates a systemic, transversal, conceptual vision that supports the complex reality of the healthcare world, where the interoperability of agents (professionals and software) is central Discusses the reuse of resources of data for knowledge improvement, health security and public health

The current scarcity of expert systems where the reasoning is based on Bayesian probability theory may be due to misconceptions about probabilities found in the literature. As argued by Cheeseman (1985), these misconceptions have led to the attitude: "The Bayesian approach doesn't work - so here is a new scheme". Several of these expert systems based on ad hoc "probability" concepts have been successful in a number of ways, demonstrating the necessity of being able to handle uncertainty in medical expert systems. They also demonstrate the need for a theoretically sound handling of uncertainty. In Andersen et al. (1986) it was postulated that knowledge organized in a causal network can be used for a unified approach to the main tasks of a medical expert system: diagnosis, planning of tests and explanations. The present paper explores this postulate in a causal probabilistic network. It also provides a practical demonstration that the problems supposedly associated with probabilistic networks are either non-existent or that practical solutions can be found. This paper reports on the methods implemented in MUNIN* -an expert system for electromyography (EMG) (Andreassen et al. 1987). EMG is the diagnosis of muscle and nerve diseases through analysis of bioelectrical signals from muscle and nerve tissue. In Andreassen et al.

This book contains 26 papers describing research in the do-main of Artificial Intelligence in Medicine. The papers aregrouped around the following themes: Methodology, knowledgerepresentation, clinical applications, modelling, uncertain-ty management, knowledge acquisition, and the user perspec-tive. The book gives an overview of the current state of AIin medicine research in Europe. It presents several techni-ques and methods that are likely to play an important rolein future applications. In the section on clinical applica-tions not only existing systems are described, but resultsof evaluation studies are presented as well.

This book contains 26 papers describing research in the do-main of Artificial Intelligence in Medicine. The papers aregrouped around the following themes: Methodology, knowledgerepresentation, clinical applications, modelling, uncertain-ty management, knowledge acquisition, and the user perspec-tive. The book gives an overview of the current state of AIin medicine research in Europe. It presents several techni-ques and methods that are likely to play an important rolein future applications. In the section on clinical applica-tions not only existing systems are described, but resultsof evaluation studies are presented as well.