Computation intelligence (CI) paradigms, including artificial neural networks, fuzzy systems, evolutionary computing techniques, and intelligent agents, form the basis of making clinical decisions. This book explains different aspects of the current research on CI technologies applied in the field of medical diagnosis. It discusses critical issues related to medical diagnosis, like uncertainties in the medical domain, problems in the medical data, especially dealing with time-stamped data, and knowledge acquisition. Features: Introduces recent applications of new computational intelligence technologies focusing on medical diagnosis issues. Reviews multidisciplinary research in health care, like data mining, medical imaging, pattern recognition, and so forth. Explores intelligent systems and applications of learning in health-care challenges, along with the representation and reasoning of clinical uncertainty. Addresses problems resulting from automated data collection in modern hospitals, with possible solutions to support medical decision-making systems. Discusses current and emerging intelligent systems with respect to evolutionary computation and its applications in the medical domain. This book is aimed at researchers, professionals, and graduate students in computational intelligence, signal processing, imaging, artificial intelligence, and data analytics.
Computation intelligence (CI) paradigms, including artificial neural networks, fuzzy systems, evolutionary computing techniques, and intelligent agents, form the basis of making clinical decisions. This book explains different aspects of the current research on CI technologies applied in the field of medical diagnosis. It discusses critical issues related to medical diagnosis, like uncertainties in the medical domain, problems in the medical data, especially dealing with time-stamped data, and knowledge acquisition. Features: Introduces recent applications of new computational intelligence technologies focusing on medical diagnosis issues. Reviews multidisciplinary research in health care, like data mining, medical imaging, pattern recognition, and so forth. Explores intelligent systems and applications of learning in health-care challenges, along with the representation and reasoning of clinical uncertainty. Addresses problems resulting from automated data collection in modern hospitals, with possible solutions to support medical decision-making systems. Discusses current and emerging intelligent systems with respect to evolutionary computation and its applications in the medical domain. This book is aimed at researchers, professionals, and graduate students in computational intelligence, signal processing, imaging, artificial intelligence, and data analytics.
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