Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2005
Reverse-engineering gene-regulatory networks using evolutionary algorithms and grid computing.
Living organisms regulate the expression of genes using complex interactions of transcription factors, messenger RNA and active protein products. Due to their complexity, gene-regulatory networks are not fully understood.However, by building computational models it is possible to gain insight into their function and operation. ⋯ Determining network models of gene-regulatory networks using evolutionary algorithms not only requires considerable computational power, but also a modeling formalism that can explain the underlying dynamics.
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The human genome project has resulted in the generation of voluminous biological data. Novel computational techniques are called for to extract useful information from this data. One such technique is that of finding patterns that are repeated over many sequences (and possibly over many species). In this paper we study the problem of identifying meaningful patterns (i.e., motifs) from biological data, the motif search problem. ⋯ All the algorithms proposed in this paper are improvements over existing algorithms for these versions of motif search in biological sequence data. The algorithms presented have the potential of performing well in practice.
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J Clin Monit Comput · Jun 2005
Reliability of near-infrared spectroscopy in people with dark skin pigmentation.
Near-infrared spectroscopy (NIRS) is a promising non-invasive technique for the continuous monitoring of tissue oxygen delivery. NIRS detects light absorbance of haemoglobin chromophores to determine tissue oxygen saturation (StO2). As skin colour is also determined by the presence of chromophores, it is plausible that NIRS signal quality may be affected by dark skin pigmentation. ⋯ In patients with a dark pigmented skin, NIRS StO2 measurements should be interpreted with caution, as melanin clearly interferes with the quality of the reflected NIRS signal.
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J Clin Monit Comput · Jun 2005
Comparative StudyA comparison of graphical and textual presentations of time series data to support medical decision making in the neonatal intensive care unit.
To compare expert-generated textual summaries of physiological data with trend graphs, in terms of their ability to support neonatal Intensive Care Unit (ICU) staff in making decisions when presented with medical scenarios. ⋯ In this experimental task, participants performed better when presented with a textual summary of the medical scenario than when it was presented as a set of trend graphs. If the necessary algorithms could be developed that would allow computers automatically to generate descriptive summaries of physiological data, this could potentially be a useful feature of decision support tools in the intensive care unit.
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J Clin Monit Comput · Jun 2005
Intraoperative monitoring using somatosensory evoked potentials. A position statement by the American Society of Neurophysiological Monitoring.
To provide an educational service to the intraoperative neurophysiologist community by publishing a position statement by the American Society of Neurophysiological Monitoring on the recommended appropriate and correct use of somatosensory evoked potentials as an intraoperative neurophysiological monitoring tool to protect patient well-being during surgery. This position statement presents the somatosensory evoked potential utilization basis, relevant anatomy, patient preparation, important systemic factors, anesthesia considerations, safety and technical considerations, documentation requirements, neurophysiologist credentials and staffing practice patterns, and monitoring applications for protecting brain, spinal nerve root, peripheral nerve, plexus and spinal cord function. In conclusion, a summary of major recommendations regarding the use of somatosensory evoked potentials in intraoperative neurophysiological monitoring is presented.