A medical informatics perspective on decision support: toward a unified research paradigm combining biological vs. clinical, empirical vs. legacy, and structured vs. unstructured data.
OBJECTIVE
To summarize current excellent research in the field of decision-support systems.


METHODS
We provide a synopsis of the articles selected for the IMIA Yearbook 2009, from which we attempt to derive a synthetic overview of the activity and new trends in the field.


RESULTS
Five papers from international peer reviewed journals have been selected for the section on decision support. While the state of the research in the field of decision-support systems is illustrated by a set of fairly heterogeneous studies, it is possible to identify trends. Thus, issues related to guidelines processing implementation occupies a central role in today's field with two alternative directions: 1. broad medical applications, which attempts to assist decision-makers to process large patient sets; 2. narrow clinical applications focused on in-depth real-time signal processing for a specific population or medical specialty.


CONCLUSIONS
The best paper selection of articles on decision-supports shows examples of excellent research on methods concerning original development as well as quality assurance of reported studies. It is also observed that this year's selection point directly to more original research areas such as temporal signal processing, although more traditionally related areas, such as information retrieval and/or natural language processing, remain fairly active in the field. Altogether these papers support the idea that more elaborated computer tools, likely to combine together textual and highly structured data, including real-time data contents, are needed.
Ruch
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University of Applied Sciences, Department of Library and Information Sciences, Geneva, Switzerland. patrick.ruch@hesge.ch
D001363:Awards and Prizes; D057225:Data Mining; D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D057286:Electronic Health Records