Systems Engineering for Medical Informatics

Data Mining in Biomedical Imaging, Signaling, and Systems ◽

10.1201/b10917-17 ◽

2011 ◽

pp. 391-415

Author(s):

Oliver Faust ◽

Chong Seong ◽

Teik-Cheng Lim ◽

Subhagata Chattopadhyay

Keyword(s):

Medical Informatics ◽

Systems Engineering

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Software Engineering Education in Medical Informatics

Methods of Information in Medicine ◽

10.1055/s-0038-1636805 ◽

1989 ◽

Vol 28 (04) ◽

pp. 295-303 ◽

Cited By ~ 1

Author(s):

F. Leven

Keyword(s):

Software Engineering ◽

Engineering Education ◽

Medical Informatics ◽

Systems Engineering ◽

Educational Status ◽

Software Engineering Education ◽

Software Methodology ◽

Practical Education ◽

Programming Paradigms ◽

The Impact

Abstract:Requirements and approaches of Software Engineering education in the field of Medical Informatics are described with respect to the impact of (1) experiences characterizing the “software misery”, (2) status and tendencies in software methodology, and (3) educational status and needs in computer science education influenced by the controversy “theoretical versus practical education”. Special attention is directed toward the growing importance of analysis, design methods, and techniques in the professional spectrum of Medical Informatics, the relevance of general principles of systems engineering in health care, the potential of non-procedural programming paradigms, and the intersection of Artificial Intelligence and education. Realizations of and experiences with programs in the field of Software Engineering are reported with respect to special requirements in Medical Informatics.

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Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making

Behavioral and Brain Sciences ◽

10.1017/s0140525x19003017 ◽

2020 ◽

Vol 43 ◽

Author(s):

Valerie F. Reyna ◽

David A. Broniatowski

Keyword(s):

Decision Making ◽

Software Engineering ◽

Systems Engineering ◽

Evidence Based ◽

Extensive Literature ◽

Trace Theory ◽

Fuzzy Trace Theory ◽

Abstract Representations ◽

Technical Systems

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.

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