Abstract
The term “digital healthcare informatics” has been coined to represent a move forward in information and communication technology-enhanced healthcare. It is a multidisciplinary field of research, at the intersection of medical sciences, biology sciences, biochemistry neurosciences, cognitive sciences and informatics. In the last years, various computational intelligence (CI) techniques and methodologies have been proposed by the researchers in order to develop digital knowledge-based systems(DKBS) for different medical and healthcare tasks. These systems are based on the knowledge engineering (KE) paradigms and artificial intelligence (AI) concepts and theories. Many types of DKBS are in existence today and are applies to different healthcare domains and tasks. The objective of the paper is to presents a comprehensive and up-to-date research in the area of digital medical decision making covering a wide spectrum of CI methodological and intelligent algorithmic issues, discussing implementations and case studies, identifying the best design practices, assessing implementation models and practices of AI paradigms in digital healthcare systems. This paper presents some of the CI techniques for managing and engineering knowledge in digital healthcare systems(DHS). Some of the research results and applications of the author and his colleagues that have been carried out in last year’s are discussed.
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Abdel-Badeeh M. Salem (2023). Computational Intelligence for Digital Healthcare Informatics. In: Zgurovsky, M., Pankratova, N. (eds) System Analysis and Artificial Intelligence . Studies in Computational Intelligence, vol 1107. Springer, Cham. https://doi.org/10.1007/978-3-031-37450-0_14
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