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Fundamentals of Clinical Data Science
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Managing Biological and Ecological Systems
Bringing together a wealth of knowledge, Environmental Management Handbook, Second Edition, gives a comprehensive overview of environmental problems, their sources, their assessment, and their solutions. Through in-depth entries and a topical table of contents, readers will quickly find answers to questions about environmental problems and their corresponding management issues. This six-volume set is a reimagining of the award-winning Encyclopedia of Environmental Management, published in 2013, and features insights from more than 400 contributors, all experts in their field. The experience, evidence, methods, and models used in studying environmental management are presented here in six sta...
Thermal Polygeneration
This textbook discusses the development and analysis of polygeneration systems to generate electricity, fresh water, hot air, cold air, and hot water from a source of energy. Topics covered in this book are desalination with no pressure or vacuum components; combined use of refrigerator and heat pump with a vapor compression refrigeration (VCR) cycle; binary fluid polygeneration; compact units; and flexible operation. It covers four polygeneration configurations, viz. binary fluid polygeneration with single-stage HDH, binary fluid polygeneration with double-stage HDH, heat pump polygeneration with single-stage HDH, and heat pump polygeneration with double-stage polygeneration. End-of-chapter problems and solved examples aid in self learning of the students. The textbook is useful for graduate and advanced graduate students studying courses such as polygeneration, sustainable energy, power generation, and alike. This book is also a useful supplementary text for researchers in fluid dynamics, thermal engineering, and allied fields.
Gas Turbines for Electric Power Generation
Everything you wanted to know about industrial gas turbines for electric power generation in one source with hard-to-find, hands-on technical information.
ECOS 2012 The 25th International Conference on Efficiency, Cost, Optimization and Simulation of Energy Conversion Systems and Processes (Perugia, June 26th-June 29th, 2012)
The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology.
Artificial Intelligence in Medical Imaging
This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-p...
Modeling Solid Oxide Fuel Cells
This book fills the need for a practical reference for all scientists and graduate students who are seeking to define a mathematical model for Solid Oxide Fuel Cell (SOFC) simulation. Structured in two parts, part one presents the basic theory, and the general equations describing SOFC operation phenomena. Part two deals with the application of the theory to practical examples, where different SOFC geometries, configurations, and different phenomena are analyzed in detail.
Head and Neck Tumor Segmentation
This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 pandemic. The 2 full and 8 short papers presented together with an overview paper in this volume were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 204 delineated PET/CT images was made available for training as well as 53 PET/CT images for testing. Various deep learning methods were developed by the participants with excellent results.
Translational Research for Better Diagnosis and Treatment of Endometrial Cancer
Endometrial cancer (EC) is the most frequent gynecological malignancy in the developed world. Optimal treatment of EC depends on early diagnosis and pre-operative stratification to appropriately select the extent of surgery and to plan further therapeutic approaches. Currently, endometrial histology is the gold standard for diagnosis, as there are no valid non-invasive methods available, and patient stratification is based on histopathology and surgical findings.
