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Methods in biomedical informatics
Seeking to cross the bridge among overview, theory, and practice, this book incorporates both methodological approaches and their potential application in the domains associated with biomedical informatics.The multi-contributor book is useful for (1) those coming from a domain seeking biomedical informatics approaches for addressing specific needs; and, (2) current biomedical informaticians seeking a foundational background for methods that might be utilized in practical scenarios germane to their ongoing research.A unique characteristic of the text is its balance between foundational coverage of core topics in biomedical informatics with practical "in-the-trenches" scenarios. Contributors represent leading experts from the biomedical informatics field: individuals who have demonstrated effective use of methodology in real-world, high-quality data applications. Contains appendices that function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4) Web Services.-
Case-based retrieval to support the treatment of end stage renal failure patients
Objective: In the present paper, we describe an application of case-based retrieval to
the domain of end stage renal failure patients, treated with hemodialysis.
Materials and methods: Defining a dialysis session as a case, retrieval of past similar
cases has to operate both on static and on dynamic features, since most of the
monitoring variables of a dialysis session are time series. Retrieval is then articulated
as a two-step procedure: (1) classification, based on static features and (2) intra-class
retrieval, in which dynamic features are considered. As regards step (2), we concentrate
on a classical dimensionality reduction technique for time series allowing for
efficient indexing, namely discrete Fourier transform (DFT). Thanks to specific index
structures (i.e. k —d trees), range queries (on local feature similarity) can be
efficiently performed on our case base, allowing the physician to examine the most
similar stored dialysis sessions with respect to the current one.
Results: The retrieval tool has been positively tested on real patients’ data, coming
from the nephrology and dialysis unit of the Vigevano hospital, in Italy.
Conclusions: The overall system can be seen as a means for supporting quality
assessment of the hemodialysis service, providing a useful input from the knowledge
management perspective
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