Jean Raymond – författare

Neuroendovascular and neurointerventional therapy is a specialty where disseminating personal knowledge and expert opinion is extremely important, owing to the lack of large-scale clinical trials. The management of complications that occur during or immediately after therapeutic interventions is particularly challenging because these can significantly affect patient outcomes. This book presents how various complication scenarios are handled by well-qualified authorities in the field of neurointervention from three disciplines: neurology, neurosurgery, and neuroradiology. Contributors describe their management of these complications, focusing on the common principles that all the specialists agree on, and give tips and tricks for 'bailout' procedures to help get the practitioner out of trouble. The book is well illustrated and covers the full range of neuroendovascular and neurointerventional procedures. The book will appeal to neurointerventionists, neuroradiologists, stroke physicians, neurosurgeons and vascular surgeons for its practical approach to managing these commonly encountered problems.

Neuroendovascular and neurointerventional therapy is a specialty where disseminating personal knowledge and expert opinion is extremely important, owing to the lack of large-scale clinical trials. The management of complications that occur during or immediately after therapeutic interventions is particularly challenging because these can significantly affect patient outcomes. This book presents how various complication scenarios are handled by well-qualified authorities in the field of neurointervention from three disciplines: neurology, neurosurgery, and neuroradiology. Contributors describe their management of these complications, focusing on the common principles that all the specialists agree on, and give tips and tricks for ''bailout'' procedures to help get the practitioner out of trouble. The book is well illustrated and covers the full range of neuroendovascular and neurointerventional procedures. The book will appeal to neurointerventionists, neuroradiologists, stroke physicians, neurosurgeons and vascular surgeons for its practical approach to managing these commonly encountered problems.

Neuroendovascular and neurointerventional therapy is a specialty where disseminating personal knowledge and expert opinion is extremely important, owing to the lack of large-scale clinical trials. The management of complications that occur during or immediately after therapeutic interventions is particularly challenging because these can significantly affect patient outcomes. This book presents how various complication scenarios are handled by well-qualified authorities in the field of neurointervention from three disciplines: neurology, neurosurgery, and neuroradiology. Contributors describe their management of these complications, focusing on the common principles that all the specialists agree on, and give tips and tricks for ''bailout'' procedures to help get the practitioner out of trouble. The book is well illustrated and covers the full range of neuroendovascular and neurointerventional procedures. The book will appeal to neurointerventionists, neuroradiologists, stroke physicians, neurosurgeons and vascular surgeons for its practical approach to managing these commonly encountered problems.

Key insights and practical guidance on transitioning to clean energy while meeting increasing energy demands, covering AI developments and more Prognostics and Health Management in Energy and Power Systems explores two highly topical subjects, energy transition and the latest advances in Artificial Intelligence, and provides insights and practical guidance for a smooth transition to clean, low-carbon energy while simultaneously continuing to meet the ever-increasing demand for energy. The first part of this book is completely devoted to the challenges, trends, and Asset Management requirements for the energy transition and explains why the energy system of the future must be resilient, autonomous, anticipatory, and situation-aware. The second part of the book presents key developments in recent years and shows the gradual shift from a collection of monolithic architectures for narrow, singular tasks to a set of modular, reconfigurable architectures capable of handling different types of tasks. An industrial case study is illustrated in the third part of the book, showing that Large-Scale Foundation models represent a promising technique to support the Prognostics and Health Management of the energy system. This book includes information on: Key differences between reliability and resilience, covering Low-Impact, High-Probability events and High-Impact, Low-Frequency eventsImportant factors in the operation of current and future power plants and substations, including software, complexity, human error, data, and maintenanceModularity, reliability, and explainability of Large-Scale Foundation modelsTransformer-based Deep Neural Networks, covering Attention Mechanisms, Positional Encoding, and input-output data embeddingGraph-based approaches to prognostics of complex machinery with sparse Run-to-Failure data, covering diagnostics feature extraction and graph dataset generationPrognostics and Health Management in Energy and Power Systems is an essential forward-thinking reference for engineers and researchers working in the energy sector with an interest in AI techniques and Machine Learning.

Key insights and practical guidance on transitioning to clean energy while meeting increasing energy demands, covering AI developments and more Prognostics and Health Management in Energy and Power Systems explores two highly topical subjects, energy transition and the latest advances in Artificial Intelligence, and provides insights and practical guidance for a smooth transition to clean, low-carbon energy while simultaneously continuing to meet the ever-increasing demand for energy. The first part of this book is completely devoted to the challenges, trends, and Asset Management requirements for the energy transition and explains why the energy system of the future must be resilient, autonomous, anticipatory, and situation-aware. The second part of the book presents key developments in recent years and shows the gradual shift from a collection of monolithic architectures for narrow, singular tasks to a set of modular, reconfigurable architectures capable of handling different types of tasks. An industrial case study is illustrated in the third part of the book, showing that Large-Scale Foundation models represent a promising technique to support the Prognostics and Health Management of the energy system. This book includes information on: Key differences between reliability and resilience, covering Low-Impact, High-Probability events and High-Impact, Low-Frequency events Important factors in the operation of current and future power plants and substations, including software, complexity, human error, data, and maintenance Modularity, reliability, and explainability of Large-Scale Foundation models Transformer-based Deep Neural Networks, covering Attention Mechanisms, Positional Encoding, and input-output data embedding Graph-based approaches to prognostics of complex machinery with sparse Run-to-Failure data, covering diagnostics feature extraction and graph dataset generation Prognostics and Health Management in Energy and Power Systems is an essential forward-thinking reference for engineers and researchers working in the energy sector with an interest in AI techniques and Machine Learning.