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Cancer du sein avancé : 29es Journées de la Société Française de Sénologie et Pathologie Mammaire (SFSPM) Avignon, 14–16 novembre 2007 = Advanced breast cancer : 29th Days of the French Society of Senology and Breast Pathology (SFSPM) Avignon, November 14–16, 2007
These days are an opportunity to remind and persuade those less convinced that the treatment of this very particular phase of the disease is not limited to a score played by a few speakers or even by medical oncologists alone; but on the contrary, we must bring into play a truly philharmonic polyphonic ensemble, united around the patient and comprising all the players in multidisciplinary care: general practitioner, surgeon, radiotherapist, imaging specialist, gynecologist, general practitioner, psychologist, algologist, supportive care workers ...
Advances in Network Electrophysiology : Using Multi-Electrode Arrays
This book book is an attempt to review the recent progress in both electronics and computational tools developed to analyze the functional operations of large ensembles of neurons and to provide the readers with a sense of the applications made possible by these technological tools. While considerable progress has been made over the last decades in our understanding of electrophysiological processes at the single channel, single synapse, and single neuron levels, our understanding of electrophysiological
Machine learning for data streams : With practical examples in MOA
The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA.
Machine Learning for Audio, Image and Video Analysis : Theory and Applications
The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text
Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms : A Practical Approach Using Python
Describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies.
Bio-inspired credit risk analysis : Computational intelligence with support vector machines
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
Bioinformatics Using Computational Intelligence Paradigms
Bioinformatics as well as Computational Intelligence are undoubtedly remarkably fast growing fields of research and real-world applications with enormous potential for current and future developments. "Bioinformatics using Computational Intelligence Paradigms" contains recent theoretical approaches and guiding applications of biologically inspired information processing systems(Computational Intelligence) against the background of bioinformatics. This carefully edited monograph combines the latest results of Bioinformatics and Computational Intelligence and offers a promising cross-fertilisation and interdisciplinary work between these growing fields.
