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Artificial Intelligence (Latest Articles)
Latest indexed articles for 'Artificial Intelligence'
Articles 61 to 70 of 200:
Predicting spontaneous termination of atrial fibrillation based on the RR interval.
30 Jul 2009 
It is important to characterize conditions under which atrial fibrillation (AF) is likely to terminate spontaneously. A novel method is proposed here. Eleven features are first extracted to characterize RR interval and Poincaré plot from a ...
rec_pub_19743637-predicting-spontaneous-termination-atrial-fibrillation-based-rr.htm
A fully complex-valued radial basis function network and its learning algorithm.
30 Jul 2009 In this paper, a fully complex-valued radial basis function (FC-RBF) network with a fully complex-valued activation function has been proposed, and its complex-valued gradient descent learning algorithm has been developed. The fully complex ...
rec_pub_19731399-a-fully-complex-valued-radial-basis-function-network-learning.htm
Prediction rules for the detection of coronary artery plaques: evidence from cardiac CT.
30 Jul 2009 OBJECTIVES: To evaluate spatial plaque distribution patterns in coronary arteries based on computed tomography coronary angiography data sets and to express the learned patterns in prediction rules. An application is proposed to use these prediction ...
rec_pub_19623688-prediction-rules-detection-coronary-artery-plaques-evidence-cardiac-ct.htm
30 Jul 2009 PURPOSE: To evaluate the reliability of global left ventricular (LV) function and mass measurements with the aid of a semi-automated (Circulation; Siemens, Forchheim, Germany) and a new fully automated software (Philips Research Europe, Aachen, ...
rec_pub_19561515-comparison-manual-semi-fully-automated-heart-segmentation-assessing.htm
Unsupervised fully automated inline analysis of global left ventricular function in CINE MR imaging.
30 Jul 2009 OBJECTIVES: To implement and evaluate the accuracy of unsupervised fully automated inline analysis of global ventricular function and myocardial mass (MM). To compare automated with manual segmentation in patients with cardiac disorders. MATERIALS ...
rec_pub_19561514-unsupervised-fully-automated-inline-analysis-global-left-ventricular.htm
30 Jul 2009 Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas ...
rec_pub_19630524-radiation-metabolomics-3-biomarker-discovery-urine-gamma-irradiated.htm
Exploration of shape variation using localized components analysis.
30 Jul 2009 Localized Components Analysis (LoCA) is a new method for describing surface shape variation in an ensemble of objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for ...
rec_pub_19542583-exploration-shape-variation-using-localized-components-analysis.htm
30 Jul 2009 In this work, we formulate the interaction between image segmentation and object recognition in the framework of the Expectation-Maximization (EM) algorithm. We consider segmentation as the assignment of image observations to object hypotheses and ...
rec_pub_19542581-synergy-object-recognition-image-segmentation-using-expectation.htm
30 Jul 2009 An algorithmic information-theoretic method is presented for object-level summarization of meaningful changes in image sequences. Object extraction and tracking data are represented as an attributed tracking graph (ATG). Time courses of object ...
rec_pub_19542574-automatic-summarization-changes-biological-image-sequences-using.htm
Efficient sparse kernel feature extraction based on partial least squares.
30 Jul 2009 The presence of irrelevant features in training data is a significant obstacle for many machine learning tasks. One approach to this problem is to extract appropriate features and, often, one selects a feature extraction method based on the ...
rec_pub_19542571-efficient-sparse-kernel-feature-extraction-based-partial-squares.htm
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