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Computational Intelligence in Medical Decision Making and Diagnosis: Techniques and ApplicationsНазвание: Computational Intelligence in Medical Decision Making and Diagnosis: Techniques and Applications
Автор: Sitendra Tamrakar, Shruti Bhargava Choubey, Abhishek Choubey
Издательство: CRC Press
Год: 2023
Страниц: 286
Язык: английский
Формат: pdf (true)
Размер: 10.05 MB

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.

The present book includes basic as well as hybrid CI techniques that have been used in recent years so as to know the current trends in medical diagnosis domain. It also presents the merits and demerits of different techniques in general as well as application-specifc context. The presented book discusses some critical issues related to medical diagnosis, like uncertainties in the medical domain, problems in medical data, especially dealing with time-stamped (temporal) data, and knowledge acquisition. In addition, this book also discusses the features of good CI techniques in medical diagnosis. It is a collection of chapters that covers a rich and diverse variety of computer-based CI techniques, all involving some aspect of Computational Intelligence, but each one taking a somewhat-pragmatic view.

Features:

Introduces recent applications of new Computation 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 Computation Intelligence, signal processing, imaging, Artificial Intelligence, and data analytics.

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