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This book contains 26 papers describing research in the do- main of Artificial Intelligence in Medicine. The papers are grouped around the following themes: Methodology, knowledge representation, clinical applications, modelling, uncertain- ty management, knowledge acquisition, and the user perspec- tive. The book gives an overview of the current state of AI in medicine research in Europe. It presents several techni- ques and methods that are likely to play an important role in future applications. In the section on clinical applica- tions not only existing systems are described, but results of evaluation studies are presented as well.

This book constitutes the refereed proceedings of the International Conference for Smart Health, ICSH 2013, held in Beijing, China, in August 2013. The 15 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on Information Sharing, Integrating and Extraction; Mining Clinical and Medical Data; Smart Health Applications.

Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 33 revised full papers presented were carefully reviewed and selected from 67 submissions. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging. It focuses on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging.

This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. The conference was organized by the Society for Artificial Neural Networks in Medicine and Biology (ANNIMAB-S), which was established to promote research within a new and genuinely cross-disciplinary field. Forty-two contributions were accepted for presentation; in addition to these, S invited papers are also included. Research within medicine and biology has often been characterised by application of statistical methods for evaluating domain specific data. The growing interest in Artificial Neural Networks has not only introduced new methods for data analysis, but also opened up for development of new models of biological and ecological systems. The ANNIMAB-l conference is focusing on some of the many uses of artificial neural networks with relevance for medicine and biology, specifically: • Medical applications of artificial neural networks: for better diagnoses and outcome predictions from clinical and laboratory data, in the processing of ECG and EEG signals, in medical image analysis, etc. More than half of the contributions address such clinically oriented issues. • Uses of ANNs in biology outside clinical medicine: for example, in models of ecology and evolution, for data analysis in molecular biology, and (of course) in models of animal and human nervous systems and their capabilities. • Theoretical aspects: recent developments in learning algorithms, ANNs in relation to expert systems and to traditional statistical procedures, hybrid systems and integrative approaches.

The Second European Conference on Artificial Intelligence in Medicine followed the successful meeting in Marseilles in 1987. As for AIME 87, the goal of AIME 89 was to promote scientific interchange within and between all subfields of AI in medicine, among researchers from all over the world, and especially from Europe. There were sessions on: knowledge elicidation and acquisition, architectures for medical knowledge-based systems, clinical applications, methodology, reasoning based on physiological models, and uncertainty. It is clear form the quality of papers presented, that the rate of development which took place between the Pavia meeting of 1985 and AIME 87 has been well maintained. With the launch of the European Community's exploratory programme in Advanced Informatics in Medicine in Europe, 1989 is clearly a very important year for this discipline. AIME 89 provided an important forum which demonstrated progress in some of the more difficult methodological problems, and advances in the application of these techniques to real-world medicine. This volume should be consulted by anyone who wishes to appreciate the state of the art in Medical AI in Europe.

In this volume, Steven Evans reports on a quarter century of work-work that resulted in a commercial product known as the PACE System. An advanced clinical management system, PACE links all care delivery set­ tings and reaches across multiple episodes. It offers capabilities critical to managed care, including care planning and clinical pathways, the critical pathway analyzer and clinical repository central to outcomes-based care, and more. The pages that follow describe the PACE project, focusing on its knowl­ edge base and semantic network. They offer insights into system implemen­ tation and address the synthesis of principles within the PACE System. From this project in nursing informatics, Steven Evans relates both suc­ cesses and failures, sharing the strategies and techniques to adopt and pitfalls to avoid in a project that followed five years of preliminary theo­ retical work. With clarity and candor, he gives us the benefit of two decades of project development, first in academia and then in the commercial sector. Over the course of the project, many tens of millions of dollars and close to 500 person-years of effort were invested. Building on the strong conceptual base developed at Creigton University's School of Nursing, the project has seen exponential growth in its clinical capabilities since entering the commercial sector in 1989.

This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: personalized stress diagnosis system, image analysis system for breast cancer diagnosis, analysis of neuronal cell images, structure prediction of protein, relationship between two mental disorders, detection of cardiac abnormalities, holistic medicine based treatment and analysis of life-science data.

This book constitutes the refereed proceedings of the 13th Conference on Artificial Intelligence in Medicine, AIME 2011, held in Bled, Slovenia, in July 2011. The 42 revised full and short papers presented together with 2 invited talks were carefully reviewed and selected from 113 submissions. The papers are organized in topical sections on knowledge-based systems; data mining; special session on AI applications; probabilistic modeling and reasoning; terminologies and ontologies; temporal reasoning and temporal data mining; therapy planning, scheduling and guideline-based care; and natural language processing.

The incursion of information and communication technologies (ICT) in health care entails evident bene?ts at the levels of security and e?ciency that improve not only the quality of life of the patients, but also the quality of the work of the health care professionals and the costs of national health care systems. Leaving research approaches aside, the analysis of ICT in health care shows an evo- tion from the initial interest in representing and storing health care data (i. e., electronic health care records) to the current interest of having remote access to electronic health care systems, as for example HL7 initiatives or telemedicine. This sometimes imperceptible evolution can be interpreted as a new step of the progress path of health care informatics, whose next emerging milestone is the convergenceof current solutions with formal methods for health care kno- edge management. In this sense, K4CARE is a European project aiming at contributing to this progress path. It is centered on the idea that health care knowledge rep- sented in a formal waymay favor the treatment of home care patients in modern societies. The project highlights several aspects that are considered relevant to the evolution of medical informatics: health care knowledge production, health care knowledge integration, update, and adaptation, and health care intelligent systems.

Artificial Intelligence in medicine is a special field of Medical Informatics and deals with the enhancement of medical information systems by knowledge based components and new paradigms. The European Society for Artificial Intelligence in Medicine Europe (AIME) was established in 1986 to foster fundamental and applied research in artificial intelligence and in symbolic information processing techniques for medical care and medical research. This book presents the proceedings of the 4th International Conference on Artificial Intelligence in Medicine (AIME93), held in Munich, Germany, in October 1993. The book contains the 26 oral presentations from the conference, as well as 38 poster presentations and two keynote speeches, and are mainly grouped around the two subject areas of knowledge acquisition and representation, and strategies for medical reasoning. Many of the papers also describe applications of AI systems in medicine. Providing a unique overview of the research and methodologies of the time, the book will be of interest to all those involved in the use of AI in medicine.