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of the Genus Chlorella. X. Products of Glucose Fermentation (S. A. Arch. Microbiol. 103) 1975. S. 13 - 19. gr8. m. zahlr. Tab. (St.) br. -2) Sonderabdruck.
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of the Genus Chlorella. X. Products of Glucose Fermentation(S. A. Arch. Microbiol. 103)1975. S. 13-19. gr8. m. Abb. br. -2) -Sonderabdruck-.
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Taschenbuch. Zustand: Neu. Efficient Data Handling for Massive Internet of Medical Things | Healthcare Data Analytics | Chinmay Chakraborty (u. a.) | Taschenbuch | xiv | Englisch | 2022 | Springer | EAN 9783030666354 | 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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ISBN 10: 3030666352 ISBN 13: 9783030666354
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of thestate-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.
Sprache: Englisch
Verlag: Springer International Publishing, 2021
ISBN 10: 3030666328 ISBN 13: 9783030666323
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of thestate-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications.The book covers among other areas:Image acquisition and formation.Computer-aided diagnosis.Image classification.Feature extraction.Image enhancement/segmentation.Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction.The key features of this book are:Machine learning and deep learning applications.Medical imaging applications.Feature extraction and analysis.Medical image classification, segmentation, recognition, and registration.Medical image analysis and enhancement.Handling medical image dataset.
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