Introduction to Computational Intelligence in Healthcare
نویسندگان
چکیده
This chapter presents introductory remarks on computational intelligence in healthcare practice, and it provides a brief outline for each of the succeeding chapters in the remainder of this book. 1.1 Computational Intelligence and Healthcare Practice Computational intelligence provides considerable promise for advancing many aspects of healthcare practice, including clinical disease management such as prevention, diagnosis, treatment, and follow-up, as well as administrative management of patients such as patient information and healthcare delivery to patients. Computational intelligence is the study of the design of intelligent agents. An intelligent agent is a system that acts intelligently—it does what it thinks appropriate for its circumstances and its goal, it is flexible to changing environments and changing goals, it learns from experience, and it makes appropriate choices given perceptual limitations and finite computation. However, computational intelligence is more than just the study of the design of intelligent agents, in particular, in application domains. It also includes the study of problems for which there are no effective algorithms, either because it is not possible to formulate them or because they are NPhard and thus not effective in real life applications. Human being (or biological organisms) can solve such problems every day with various degrees of competence: extracting meaning from perception, understanding language, and solving ill-defined computer vision problems. Thus, the central scientific goal of computational intelligence is to understand the principles that make intelligent behavior possible, whether in natural or in artificial systems. The central engineering goal of computational intelligence is to specify methods for the design of useful, intelligent artifacts. Indeed, the core methods of computational intelligence—neural computing, fuzzy systems, and evolutionary computing—have recently emerged as promising tools for H. Yoshida et al.: Introduction to Computational Intelligence in Healthcare, Studies in Computational Intelligence (SCI) 65, 1–4 (2007) www.springerlink.com c © Springer-Verlag Berlin Heidelberg 2007
منابع مشابه
The Correlation between demographic characteristics, emotional intelligence and conflict management strategies in managers of different organizational levels in hospitals affiliated to Tehran University of Medical Sciences
Introduction: Hospitals have conflicts because of their complex nature, so they need managers with high emotional intelligence for effective conflict management. There are contradictory results in the correlations between demographic characteristics, emotional intelligence and conflict management; therefore, this study was conducted to investigate the correlation between them in different manag...
متن کاملArtificial Intelligence in Healthcare
The article is a letter to the editor, so it has no abstract.
متن کاملAdvanced Computational Intelligence Paradigms in Healthcare - 2
Reading is a hobby to open the knowledge windows. Besides, it can provide the inspiration and spirit to face this life. By this way, concomitant with the technology development, many companies serve the e-book or book in soft file. The system of this book of course will be much easier. No worry to forget bringing the advanced computational intelligence paradigms in healthcare 2 book. You can op...
متن کاملAdvanced Computational Intelligence Paradigms in Healthcare - 1
We may not be able to make you love reading, but advanced computational intelligence paradigms in healthcare 1 will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you the kindness. In ...
متن کاملArtificial Intelligence Tools in Health Information Management
Application of ICT in health (eHealth) has become an integral part of modern healthcare systems. Electronic health information management has proven useful in improving quality of health care, reducing costs and facilitating health research. However, the increasing complexity of healthcare and the growing demand for high quality healthcare delivery has created a need for eHealth systems with t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007