This book focuses on approaches to computer-assisted medical decision-making. A unique feature of the book is that a specific problem in medical decision-making has been selected from the literature, with each contributed chapter presenting a different approach to the solution of the same problem. Theoretical foundations for each approach are provided, followed by practical application. Techniques include knowledge-based reasoning, neural network models, hybrid systems, reasoning with uncertainty, and fuzzy logic, among others. The goal is to supply the reader with a variety of theoretical techniques whose practical implementation can be clearly understood through the example. Using a single, concrete example to illustrate different theoretical approaches allows various techniques to be easily contrasted and permits the reader to determine which aspects are pertinent to specific types of applications. Although the methods are illustrated in a medical problem, they have wide applicability in numerous areas of decision-making.

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This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.

"This book covers state-of-the-art applications in many areas of medicine and healthcare"--Provided by publisher.

These two volumes consisting of Foundations and Applications provide the current status of theoretical and empirical developments in "computing with words". In philosophy, the twentieth century is said to be the century of language. This is mainly due to Wittgenstein who said: "The meaning of a word is its use in the language game". "The concept game is a concept with blurred edges". In the first phrase, "the language game" implies the everyday human activity with language, and in the latter, "game" simply implies an ordinary word. Thus, Wittgenstein precisely stated that a word is fuzzy in real life. Unfortunately this idea about a word was not accepted in the conventional science. We had to wait for Zadeh's fuzzy sets theory. Remembering Wittgenstein's statement, we should consider, on the one hand, the concept of "computing with words" from a philosophical point of view. It deeply relates to the everyday use of a word in which the meaning of a word is fuzzy in its nature.

Essays in honour of John Bell on the art of comparative law, focussing on the manner of 'legal development'.

Using examples drawn from biomedicine and biomedical engineering, this essential reference book brings you comprehensive coverage of all the major techniques currently available to build computer-assisted decision support systems. You will find practical solutions for biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision aids, including hybrid systems. Neural Networks and Artificial Intelligence for Biomedical Engineering offers students and scientists of biomedical engineering, biomedical informatics, and medical artificial intelligence a deeper understanding of the powerful techniques now in use with a wide range of biomedical applications. Highlighted topics include: Types of neural networks and neural network algorithms Knowledge representation, knowledge acquisition, and reasoning methodologies Chaotic analysis of biomedical time series Genetic algorithms Probability-based systems and fuzzy systems Evaluation and validation of decision support aids

In the late eighties of the twentieth century I encountered a paper referring to mathematics dealing with imprecision applied to medical diagnosis. I was working in the area of medical statistics at that time, and obviously I was interested in the contents of the paper. After I had read it I became fascinated by new possibilities of medical data interpretation and processing proposed by the author. The new world of fuzziness, originated by Professor Lotfi Zadeh, seemed to open up to me and I started reading all accessible material about fuzzy set theory. Many years have passed since then. We are now living in the information so- ety and we do not experience troubles in reaching scientific material. Lately I have read many papers and books about treating medical tasks solved by using fuzzy ideas. I am still keen on tracing applications in medicine, and by myself I have been contributing to some concepts in this subject that has motivated me to p- pare my own book. The objective of writing such a book has been a little parti- lar, namely, I have intended to present the subject of fuzzy tools and techniques in medicine for eventual users. These, maybe representatives of medical or phar- cological staffs, are not expected to possess a large amount of mathematical knowledge.

Over the last century, medicine has come out of the "black bag" and emerged as one of the most dynamic and advanced fields of development in science and technology. Today, biomedical engineering plays a critical role in patient diagnosis, care, and rehabilitation. More than ever, biomedical engineers face the challenge of making sure that medical d