SEARCH · PubMed Health

Results for “Algorithms”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50Linked to original sources

PubMed2004

Canadian 2003 International Consensus Algorithm For the Diagnosis, Therapy, and Management of Hereditary Angioedema.

C1 inhibitor deficiency (hereditary angioedema [HAE]) is a rare disorder for which there is a lack of consensus concerning diagnosis, therapy, and management, particularly in Canada. European initiatives have driven the approach to managing HAE with 3 C1-INH Deficiency Workshops held every 2 years in Hungary starting in 1999, with the third Workshop having recently been held in May 2003. The European Contact Board has established a European HAE Registry that will hopefully advance our knowledge of this disorder. The Canadian Hereditary Angioedema Society/Société d'Angioédème Héréditaire du Canada organized a Canadian International Consensus Conference held in Toronto, Ontario, Canada, on October 24 to 26, 2003, to foster consensus between major European and North American HAE treatment centers. Papers were presented by investigators from Europe and North America, and this consensus algorithm approach was discussed. There is a paucity of double-blind placebo-controlled trials in the treatment of HAE, making levels of evidence to support the algorithm less than optimal. Enclosed is the consensus algorithm approach recommended for the diagnosis, therapy, and management of HAE and agreed to by the authors of this article. This document is only a consensus algorithm approach and requires validation. As such, participants agreed to make this a living 2003 algorithm (ie, a work in progress) and agreed to review its content at future international HAE meetings. The consensus, however, has strength in that it was arrived at by the meeting of patient-care providers along with patient group representatives and individual patients reviewing information available to date and reaching agreement on how to approach the diagnosis, therapy, and management of HAE circa 2003. Hopefully evidence to support approaches to the management of HAE will approach the level of meta-analysis of randomized controlled trials in the near future.

Algorithms↗

PubMed2004

A computer algorithm for representing spatial-temporal structure of human motion and a motion generalization method.

Inspired by the generalized motor program (GMP) theory, this study presents a symbolic motion structure representation (SMSR) algorithm that identifies a basic spatial-temporal structure of a human motion. The algorithm resolves each joint angle-time trajectory of a multi-joint motion into a sequence of elemental motion segments and labels each motion segment with a symbol representing its shape ("U": monotonically increasing; "D": monotonically decreasing; "S": stationary). By concatenating symbols according to their order in time, the spatial-temporal structure of a joint angle-time trajectory is represented as a symbolic string. The structure of a multi-joint motion is then represented as a set of symbolic strings. A sample motion, whose structure is identified by the SMSR algorithm, can be generalized to produce an infinite number of similar motion variants. To generate a variant of a sample motion, segment boundary points of the sample motion are first relocated to new locations in the angle-time space, and then individual motion segments of the original joint angle trajectories are shifted and proportionally rescaled to fit the new segment boundary points. This motion generalization method provides a basis for developing GMP-based motion simulation models, and exploring ideas and hypotheses related to the GMP theory through simulation. As an application of the motion generalization method, a motion modification (MoM) algorithm is presented, which adapts existing reach motions for new target locations. Some examples generated by the MoM algorithm are illustrated.

Algorithms↗

PubMed2005

A robust algorithm for the simultaneous parameter estimation of interfacial tension and contact angle from sessile drop profiles.

The pendant and sessile drop profile analysis using the finite element method (PSDA-FEM) is an algorithm which allows simultaneous determination of the interfacial tension (gamma) and contact angle (theta(c)) from sessile drop profiles. The PSDA-FEM algorithm solves the nonlinear second-order spherical coordinate form of the Young-Laplace equation. Thus, the boundary conditions at the drop apex and contact position of the drop with the substrate are required to solve for the drop profile coordinates. The boundary condition at the position where the drop contacts the substrate may be specified as a fixed contact line or fixed contact angle. This paper will focus on the fixed contact angle boundary condition for sessile drops on a substrate and how this boundary condition is used in the PSDA-FEM curve-fitting algorithm. The PSDA-FEM algorithm has been tested using simulated drop shapes with and without the addition of random error to the drop profile coordinates. The random error is varied to simulate the effect of camera resolution on the estimates of gamma and theta(c) values obtained from the curve-fitting algorithm. The error in the experimental values for gamma from sessile drops of water on acrylic and Mazola corn oil on acrylic falls within the predicted range of errors obtained for gamma values from simulated sessile drop profiles with randomized errors that are comparable in magnitude to the resolution of the experimental setup.

Algorithms↗

PubMed2006

A simple algorithm for defining the mechanism and the chamber of origin in atrial tachycardias.

INTRODUCTION: Although macroreentrant atrial tachycardia (MRAT) and focal atrial tachycardia (FAT) can be successfully cured by catheter ablation, the proper diagnosis and treatment of these arrhythmias can still be challenging. AIM: The objective of this study is to develop an algorithm allowing rapid diagnosis of the mechanism and the chamber of origin of atrial tachycardia based on intracardiac catheter recordings from the right atrium and the coronary sinus (CS). METHODS: A 2-stepped algorithm was designed: (1) The time of biatrial activation expressed as a percentage of the tachycardia cycle length served to discriminate FAT from MRAT. (2) In FAT, the direction of activation of the CS catheter and the earliest atrial activation were used to define the chamber of origin. In MRAT, the time of right atrium activation was determined or entrainment was used at different sites. Thirty-two intracardiac recordings were reviewed off-line after the algorithm by 4 electrophysiologists blinded to the mechanism and the chamber of origin. The results of their analysis were compared with the intraoperative diagnosis. RESULTS: The algorithm correctly identified 11 (100%) of 11 FATs and 19 (90.4%) of 21 MRATs. The site of origin was correctly identified in 8 (72.7%) of 11 FATs and in 20 of 21 (95.2%) MRATs. The site of origin was misidentified in 3 FATs, all arising from the CS ostium. CONCLUSIONS: This algorithm allows rapid discrimination between FAT and MRAT. The chamber of origin is detected with a high accuracy in MRAT. However, the earliest atrial activation taken as an isolated event is not a good predictor for the chamber of origin in FAT arising from the ostium of the CS.

Algorithms↗

PubMed2006

An algorithm for continuous real-time QT interval monitoring.

QT interval measurement in the patient monitoring environment is receiving much interest because of the potential for proarrhythmic effects from both cardiac and noncardiac drugs. The American Heart Association and American Association of Critical Care Nurses practice standards for ECG monitoring in hospital settings now recommend frequent monitoring of QT interval when patients are started on a potentially proarrhythmic drug. We developed an algorithm to continuously measure QT interval in real-time in the patient monitoring setting. This study reports our experience in developing and testing this automated QT algorithm. Compared with the environment of resting ECG analysis, real-time ECG monitoring has a number of challenges: significantly more amounts of muscle and motion artifact, increased baseline wander, a varied number and location of ECG leads, and the need for trending and for alarm generation when QT interval prolongation is detected. We have used several techniques to address these challenges. In contiguous 15-second time windows, we average the signal of tightly clustered normal beats detected by a real-time arrhythmia-monitoring algorithm to minimize the impact of artifact. Baseline wander is reduced by zero-phase high-pass filtering and subtraction of isoelectric points as determined by median signal values in a localized region. We compute a root-mean-squared ECG waveform from all available leads and use a novel technique to measure the QT interval. We have tested this algorithm against standard and proprietary ECG databases. Our real-time QT interval measurement algorithm proved to be stable, accurate, and able to track changing QT values.

Algorithms↗

PubMed2006

LAI inversion algorithm based on directional reflectance kernels.

Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.

Algorithms↗

PubMed2006

Stepwise combination algorithms of non-invasive markers to diagnose significant fibrosis in chronic hepatitis C.

BACKGROUND/AIMS: In chronic hepatitis C, biopsy is the gold standard for assessment of liver fibrosis. Non-invasive markers have been proposed but their use is limited by diagnostic accuracy. Our aim was to increase the diagnostic performance of non-invasive markers of liver fibrosis by combining them in sequential algorithms. METHODS: One hundred and ninety patients with chronic hepatitis C were evaluated for AST to platelets ratio (APRI), Forns' index and Fibrotest at the time of liver biopsy and stepwise combination algorithms were developed and validated prospectively in 100 additional patients. RESULTS: Three algorithms were developed: (1) significant fibrosis (F>or=2 by METAVIR) was identified with high diagnostic performance (>94% accuracy) using APRI as screening test, followed by Fibrotest in APRI non-classified cases and restricting liver biopsy to patients classified F0-F1 by non-invasive tests. (2) A slightly modified algorithm had similar performance when applied to hepatitis C carriers with normal ALT. (3) Identification of cirrhosis (95% accuracy) was achieved using a dedicated algorithm with different cut-off, reducing by 60-70% the liver biopsies needed. CONCLUSIONS: Stepwise combination of non-invasive markers of liver fibrosis improves the diagnostic performance in chronic hepatitis C. Need for liver biopsy is reduced by 50-70% but cannot be completely avoided.

Adult↗

PubMed2004

A new theory and algorithm for reconstructing helical structures with a seam.

Conventional helical reconstruction is a general method to obtain three-dimensional structures of many filamentous biological macromolecules. The method assumes helical symmetry, and generates the three-dimensional structures from two-dimensional projection images. However, the theory is inadequate to describe filamentous structures discontinuities, which are called seams in the case of microtubules or perturbations in the case of tobacco mosaic virus or the bacterial flagellar filament. To study such structures, a new theory and algorithm are required. To this aim, we developed a new algorithm, namely, asymmetric helical reconstruction, which is based on our new theory that describes a "helical" object with a seam. In the theory, "helical" objects with a seam are indexed with a non-integral order of nu. Like the conventional helical reconstruction, the layer-line data are extracted from the Fourier transform of the images. We show that the Fourier-Bessel transform using the Bessel functions of fractional order can, to good approximation, reconstruct the three-dimensional structure of the object. To test the new algorithm, we reconstructed three-dimensional structures of a kinesin-microtubule complex with a seam from both model data and experimental data from cryo-electron microscopic images. The reconstructed structures are almost identical with those reconstructed from conventional helical reconstruction demonstrating the validity of the algorithm. The algorithm enables the analysis of various "helical" specimens with seams and also significantly improves the throughput and the resolution of kinesin-microtubule complexes.

Algorithms↗

PubMed2004

Design and validation of a computer-based sleep-scoring algorithm.

A computer-based sleep scoring algorithm was devised for the real time scoring of sleep-wake state in Wistar rats. Electroencephalogram (EEG) amplitude (microV(rms)) was measured in the following frequency bands: delta (delta; 1.5-6 Hz), theta (Theta; 6-10 Hz), alpha (alpha; 10.5-15 Hz), beta (beta; 22-30 Hz), and gamma (gamma; 35-45 Hz). Electromyographic (EMG) signals (microV(rms)) were recorded from the levator auris longus (neck) muscle, as this yielded a significantly higher algorithm accuracy than the spinodeltoid (shoulder) or temporalis (head) muscle EMGs (ANOVA; P=0.009). Data were obtained using either tethers (n=10) or telemetry (n=4). We developed a simple three-step algorithm that categorizes behavioural state as wake, non-rapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, based on thresholds set during a manually-scored 90-min preliminary recording. Behavioural state was assigned in 5-s epochs. EMG amplitude and ratios of EEG frequency band amplitudes were measured, and compared with empirical thresholds in each animal.STEP 1: EMG amplitude greater than threshold? Yes: "active" wake, no: sleep or "quiet" wake. STEP 2: EEG amplitude ratio (delta x alpha)/(beta x gamma) greater than threshold? Yes: NREM, no: REM or "quiet" wake. STEP 3: EEG amplitude ratio Theta(2)/(delta x alpha) greater than threshold? Yes: REM, no: "quiet" wake. The algorithm was validated with one, two and three steps. The overall accuracy in discriminating wake and sleep (NREM and REM combined) using step one alone was found to be 90.1%. Overall accuracy using the first two steps was found to be 87.5% in scoring wake, NREM and REM sleep. When all three steps were used, overall accuracy in scoring wake, NREM and REM sleep was determined to be 87.9%. All accuracies were derived from comparisons with unequivocally-scored epochs from four 90-min recordings as defined by an experienced human rater. The algorithms were as reliable as the agreement between three human scorers (88%).

Algorithms↗

PubMed2004

Neural spike classification using parallel selection of all algorithm parameters.

The Forster-Handwerker template-matching algorithm (J. Neurosci. Methods 31 (1990) 109) classifies neuronal spikes according to three parameters selected by the experimenter prior to running the algorithm. Thousands of different combinations of these parameter values are possible producing hundreds of different classifications for each input file. Using a 40-processor Linux-based parallel computing cluster, we ran their algorithm with an effective sampling of all combinations of parameter values in order to generate a list of the classifications that can be generated by the algorithm. A distance measure was used to quantify the similarity between classifications and then to create a distance table containing entries for the distances between all pairs of classifications. Using a self-organizing neural network (SON) and the distance table we group the classifications by similarity and select the best representative classifications that the Forster-Handwerker algorithm can produce.

Action Potentials↗

PubMed2005

Quantitative comparison of algorithms for inter-subject registration of 3D volumetric brain MRI scans.

The objective of inter-subject registration of three-dimensional volumetric brain scans is to reduce the anatomical variability between the images scanned from different individuals. This is a necessary step in many different applications such as voxelwise group analysis of imaging data obtained from different individuals. In this paper, the ability of three different image registration algorithms in reducing inter-subject anatomical variability is quantitatively compared using a set of common high-resolution volumetric magnetic resonance imaging scans from 17 subjects. The algorithms are from the automatic image registration (AIR; version 5), the statistical parametric mapping (SPM99), and the automatic registration toolbox (ART) packages. The latter includes the implementation of a non-linear image registration algorithm, details of which are presented in this paper. The accuracy of registration is quantified in terms of two independent measures: (1) post-registration spatial dispersion of sets of homologous landmarks manually identified on images before or after registration; and (2) voxelwise image standard deviation maps computed within the set of images registered by each algorithm. Both measures showed that the ART algorithm is clearly superior to both AIR and SPM99 in reducing inter-subject anatomical variability. The spatial dispersion measure was found to be more sensitive when the landmarks were placed after image registration. The standard deviation measure was found sensitive to intensity normalization or the method of image interpolation.

Adult↗

PubMed2006

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG).

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Aged↗

PubMed2006

Prediction of collagen orientation in articular cartilage by a collagen remodeling algorithm.

OBJECTIVE: Tissue engineering is a promising method to treat damaged cartilage. So far it has not been possible to create tissue-engineered cartilage with an appropriate structural organization. It is envisaged that cartilage tissue engineering will significantly benefit from knowledge of how the collagen fiber orientation is directed by mechanical conditions. The goal of the present study is to evaluate whether a collagen remodeling algorithm based on mechanical loading can be corroborated by the collagen orientation in healthy cartilage. METHODS: According to the remodeling algorithm, collagen fibrils align with a preferred fibril direction, situated between the positive principal strain directions. The remodeling algorithm was implemented in an axisymmetric finite element model of the knee joint. Loading as a result of typical daily activities was represented in three different phases: rest, standing and gait. RESULTS: In the center of the tibial plateau the collagen fibrils run perpendicular to the subchondral bone. Just below the articular surface they bend over to merge with the articular surface. Halfway between the center and the periphery, the collagen fibrils bend over earlier, resulting in a thicker superficial and transitional zones. Near the periphery fibrils in the deep zone run perpendicular to the articular surface and slowly bend over to angles of -45 degrees and +45 degrees with the articular surface. CONCLUSION: The collagen structure as predicted with the collagen remodeling algorithm corresponds very well with the collagen structure in healthy knee joints. This remodeling algorithm is therefore considered to be a valuable tool for developing loading protocols for tissue engineering of articular cartilage.

Algorithms↗

PubMed2005

Unified 3-D structure and projection orientation refinement using quasi-Newton algorithm.

We describe an algorithm for simultaneous refinement of a three-dimensional (3-D) density map and of the orientation parameters of two-dimensional (2-D) projections that are used to reconstruct this map. The application is in electron microscopy, where the 3-D structure of a protein has to be determined from a set of 2-D projections collected at random but initially unknown angles. The design of the algorithm is based on the assumption that initial low resolution approximation of the density map and reasonable guesses for orientation parameters are available. Thus, the algorithm is applicable in final stages of the structure refinement, when the quality of the results is of main concern. We define the objective function to be minimized in real space and solve the resulting nonlinear optimization problem using a Quasi-Newton algorithm. We calculate analytical derivatives with respect to density distribution and the finite difference approximations of derivatives with respect to orientation parameters. We demonstrate that calculation of derivatives is robust with respect to noise in the data. This is due to the fact that noise is annihilated by the back-projection operations. Our algorithm is distinguished from other orientation refinement methods (i) by the simultaneous update of the density map and orientation parameters resulting in a highly efficient computational scheme and (ii) by the high quality of the results produced by a direct minimization of the discrepancy between the 2-D data and the projected views of the reconstructed 3-D structure. We demonstrate the speed and accuracy of our method by using simulated data.

Algorithms↗

PubMed2005

A model-based parallel origin and orientation refinement algorithm for cryoTEM and its application to the study of virus structures.

We present a model-based parallel algorithm for origin and orientation refinement for 3D reconstruction in cryoTEM. The algorithm is based upon the Projection Theorem of the Fourier Transform. Rather than projecting the current 3D model and searching for the best match between an experimental view and the calculated projections, the algorithm computes the Discrete Fourier Transform (DFT) of each projection and searches for the central section ("cut") of the 3D DFT that best matches the DFT of the projection. Factors that affect the efficiency of a parallel program are first reviewed and then the performance and limitations of the proposed algorithm are discussed. The parallel program that implements this algorithm, called PO(2)R, has been used for the refinement of several virus structures, including those of the 500 Angstroms diameter dengue virus (to 9.5 Angstroms resolution), the 850 Angstroms mammalian reovirus (to better than 7A), and the 1800 Angstroms paramecium bursaria chlorella virus (to 15 Angstroms).

Algorithms↗

PubMed2006

Strategies for adapting automated seizure detection algorithms.

The time-varying dynamics of epileptic seizures and the high inter-individual variability make their detection difficult. Osorio et al. [Osorio, I, Frei, MG, Wilkinson, SB. Real-time automated detection and quantitative analysis of seizures and short-term prediction of clinical onset. Epilepsia 1998;39(6):615-27] developed an algorithm that has had success in detecting seizures. We present a new strategy for adapting this algorithm or other algorithms to an individual's seizure fingerprint using both seizure and non-seizure training segments and a novel performance criterion that directly incorporates the non-linearity and lack of differentiability of the algorithm. The joint optimization of a linear filter chosen from a bank of candidate filters and of a percentile used in order statistic filtering provides an empirical solution that is both practical and useful, which should translate into improved sensitivity, specificity and detection speed. This premise is strongly supported by the results obtained in a large validation study and the examples illustrated in this article. This strategy is generalizable to other detection algorithms with modular architecture and spectral filters.

Algorithms↗

PubMed2004

Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm.

In this paper an automatic atlas-based segmentation algorithm for 4D cardiac MR images is proposed. The algorithm is based on the 4D extension of the expectation maximisation (EM) algorithm. The EM algorithm uses a 4D probabilistic cardiac atlas to estimate the initial model parameters and to integrate a priori information into the classification process. The probabilistic cardiac atlas has been constructed from the manual segmentations of 3D cardiac image sequences of 14 healthy volunteers. It provides space and time-varying probability maps for the left and right ventricles, the myocardium, and background structures such as the liver, stomach, lungs and skin. In addition to using the probabilistic cardiac atlas as a priori information, the segmentation algorithm incorporates spatial and temporal contextual information by using 4D Markov Random Fields. After the classification, the largest connected component of each structure is extracted using a global connectivity filter which improves the results significantly, especially for the myocardium. Validation against manual segmentations and computation of the correlation between manual and automatic segmentation on 249 3D volumes were calculated. We used the 'leave one out' test where the image set to be segmented was not used in the construction of its corresponding atlas. Results show that the procedure can successfully segment the left ventricle (LV) (r = 0.96), myocardium (r = 0.92) and right ventricle (r = 0.92). In addition, 4D images from 10 patients with hypertrophic cardiomyopathy were also manually and automatically segmented yielding a good correlation in the volumes of the LV (r = 0.93) and myocardium (0.94) when the atlas constructed with volunteers is blurred.

Algorithms↗

PubMed2005

An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies.

Quantitative cerebral blood flow (CBF) values can be determined from residue function estimates obtained from magnetic resonance dynamic susceptibility contrast (DSC) perfusion studies using a variety of deconvolution approaches. However, there are significant differences between the CBF estimates obtained, differences that are not simply due to minor details of the implementation of the algorithms. The standard singular value decomposition (sSVD) shows a variation of CBF values with arterial-tissue delay (ATD) not present with the Fourier transform deconvolution algorithm. Fourier transform deconvolution and the newly suggested delay-invariant SVD algorithm implementations provide CBF estimates whose accuracy changes with tissue mean transit times (MTTs). Techniques combining sSVD with deliberate ATD manipulation have been proposed to compensate for this inaccuracy. Other studies indicate that CBF changes related to slice position in a multislice study, and other experimental factors, can be reduced using interpolative deconvolution algorithms. In this review, we use both time-domain and frequency-domain analysis to show the underlying theoretical relationships between these many approaches to obtain "the best" CBF estimate. This model allows us to better understand the similarities and differences, advantages and disadvantages between these variants of the deconvolution algorithms used in DSC perfusion studies.

Algorithms↗