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Stefan V Pantazi

Publications and source records attributed to Stefan V Pantazi.

2 recordsLinked to original sources

The usability axiom of medical information systems.

INTRODUCTION: In this article we begin by connecting the concept of simplicity of user interfaces of information systems with that of usability, and the concept of complexity of the problem-solving in information systems with the concept of usefulness. We continue by stating "the usability axiom" of medical information technology: information systems must be, at the same time, usable and useful. We then try to show why, given existing technology, the axiom is a paradox and we continue with analysing and reformulating it several times, from more fundamental information processing perspectives. DISCUSSION: We underline the importance of the concept of representation and demonstrate the need for context-dependent representations. By means of thought experiments and examples, we advocate the need for context-dependent information processing and argue for the relevance of algorithmic information theory and case-based reasoning in this context. Further, we introduce the notion of concept spaces and offer a pragmatic perspective on context-dependent representations. We conclude that the efficient management of concept spaces may help with the solution to the medical information technology paradox. Finally, we propose a view of informatics centred on the concepts of context-dependent information processing and management of concept spaces that aligns well with existing knowledge centric definitions of informatics in general and medical informatics in particular. In effect, our view extends M. Musen's proposal and proposes a definition of Medical Informatics as context-dependent medical information processing. SUMMARY: The axiom that medical information systems must be, at the same time, useful and usable, is a paradox and its investigation by means of examples and thought experiments leads to the recognition of the crucial importance of context-dependent information processing. On the premise that context-dependent information processing equates to knowledge processing, this view defines Medical Informatics as a context-dependent medical information processing which aligns well with existing knowledge centric definitions of our field.

Algorithms↗

Case-based medical informatics.

BACKGROUND: The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. DISCUSSION: We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging.Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. SUMMARY: Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately.

Decision Support Systems, Clinical↗