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This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
This book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life. It contains coverage of the relevant data sources available for model construction (panomics), ranging from clinical or preclinical resources to basic patient and treatment characteristics, medical imaging (radiomics), and molecular biological markers such as those involved in genomics, proteomics and metabolomics. It also includes discussions on the varying methodologies for predictive model building with analytical and data-driven ...
"This book provides a comprehensive overview of machine learning research and technology in medical decision-making based on medical images"--Provided by publisher.
This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004, held in Exeter, UK, in August 2004. The 124 revised full papers presented were carefully reviewed and selected from 272 submissions. The papers are organized in topical sections on bioinformatics, data mining and knowledge engineering, learning algorithms and systems, financial engineering, and agent technologies.
As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.
In radiation oncology as in many other specialties clinical trials are essential to investigate new therapy approaches. Usually, preparation for a prospective clinical trial is extremely time consuming until ethics approval is obtained. To test a new treatment usually many years pass before it can be implemented in the routine care. During that time, already new interventions emerge, new drugs appear on the market, technical & physical innovations are being implemented, novel biology driven concepts are translated into clinical approaches while we are still investigating the ones from years ago. Another problem is associated with molecular diagnostics and the growing amount of tumor specific...
This book provides an up-to-date comprehensive overview of the exciting new developments shaping the current and future practice of radiation oncology. Advances in treatment planning and delivery, in biological targeted therapies combined with radiation and in functional and molecular imaging are all covered in a single volume. All of these advances are discussed by leading experts in the field and with a critical evaluation of their clinical relevance throughout.
Reflecting the increased importance of the collaborations between radiation oncology and informatics professionals, Informatics in Radiation Oncology discusses the benefits of applying informatics principles to the processes within radiotherapy. It explores how treatment and imaging information is represented, stored, and retrieved as well as how this information relates to other patient data. The book deepens your knowledge of current and emerging information technology and informatics principles applied to radiation oncology so that all the data gathered—from laboratory results to medical images—can be fully exploited to make treatments more effective and processes more efficient. Afte...
"This book is specific to the field of medical informatics and ubiquitous health care and highlights the use of new trends based on the new initiatives of Web 2.0"--Provided by publisher.
An oft-neglected subject, right-wing women are an important component in understanding the many racist, fascist, and anti-feminist movements of the 20th century. Providing original research on an array of right-wing groups around the world, the contributors paint a disturbing and complicated portrait of the women involved in these movements. From Mussolini supporters to Klanswomen, this collection provides an eye-opening look at extremist women.