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2 produkter
552 kr
Skickas inom 5-8 vardagar
Breast cancer affects 1 in 10 women and the majority of UK women will attend a breast clinic at least once during their lives. The patient's journey through assessment and management is one that involves a huge range of healthcare professionals, in which the truly multidisciplinary management style required has previously been only sparsely addressed. This book provides a practical guide on how to investigate and manage common breast problems for all members of the breast disease team, whether surgeons, nurses, pathologists or support workers. Its focus is on providing easy access to the most up-to-date evidence, allowing healthcare workers to make the best decisions possible and encouraging a team approach to patient support.26 chapters cover the whole of the patient journey from assessment through to surgery and adjuvant treatments, giving a practical overview of the whole process of care. The coverage guides the reader from clinical examination and investigation of the breast patient to pre-operative workup and post-operative complication guidance. To enable swift and effective decision-making, clear management plans are provided for common breast problems. The book also includes the latest evidence, guidance and references on breast disease, together with discussions on current controversies in the field including the management of margins, management of the axilla and the evidence surrounding the NHS Breast Screening Programme. To give practical advice on the realities of being part of a breast care team, the book also has several chapters devoted to leadership and management including MDT requirements, audit and research, avoiding complaints and the organisation of a breast unit.Enabling every healthcare professional to respond to patients' needs accurately and knowledgeably, Breast Disease Management is a practical guide for the whole team in providing truly patient-centred, effective care.
882 kr
Skickas inom 7-10 vardagar
This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study.A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code.Chris Bishop is a Technical Fellow at Microsoft and is the Director of Microsoft Research AI4Science. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society. Hugh Bishop is an Applied Scientist at Wayve, a deep learning autonomous driving company in London, where he designs and trains deep neural networks. He completed his MPhil in Machine Learning and Machine Intelligence at Cambridge University.“Chris Bishop wrote a terrific textbook on neural networks in 1995 and has a deep knowledge of the field and its core ideas. His many years of experience in explaining neural networks have made him extremely skillful at presenting complicated ideas in the simplest possible way and it is a delight to see these skills applied to the revolutionary new developments in the field.” -- Geoffrey Hinton"With the recent explosion of deep learning and AI as a research topic, and the quickly growing importance of AI applications, a modern textbook on the topic was badly needed. The "New Bishop" masterfully fills the gap, covering algorithms for supervised and unsupervised learning, modern deep learning architecture families, as well as how to apply all of this to various application areas." – Yann LeCun“This excellent and very educational book will bring the reader up to date with the main concepts and advances in deep learning with a solid anchoring in probability. Theseconcepts are powering current industrial AI systems and are likely to form the basis of further advances towards artificial general intelligence.” -- Yoshua Bengio