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At least 451 records · Page 25Linked to original sources

PubMed2004

Multi-detector row computed tomography of the heart: does a multi-segment reconstruction algorithm improve left ventricular volume measurements?

A multi-segment cardiac image reconstruction algorithm in multi-detector row computed tomography (MDCT) was evaluated regarding temporal resolution and determination of left ventricular (LV) volumes and global LV function. MDCT and cine magnetic resonance (CMR) imaging were performed in 12 patients with known or suspected coronary artery disease. Patients gave informed written consent for the MDCT and the CMR exam. MDCT data were reconstructed using the standard adaptive cardiac volume (ACV) algorithm as well as a multi-segment algorithm utilizing data from three, five and seven rotations. LV end-diastolic (LV-EDV) and end-systolic volumes and ejection fraction (LV-EF) were determined from short-axis image reformations and compared to CMR data. Mean temporal resolution achieved was 192+/-24 ms using the ACV algorithm and improved significantly utilizing the three, five and seven data segments to 139+/-12, 113+/-13 and 96+/-11 ms (P<0.001 for each). Mean LV-EDV was without significant differences using the ACV algorithm, the multi-segment approach and CMR imaging. Despite improved temporal resolution with multi-segment image reconstruction, end-systolic volumes were less accurately measured (mean differences 3.9+/-11.8 ml to 8.1+/-13.9 ml), resulting in a consistent underestimation of LV-EF by 2.3-5.4% in comparison to CMR imaging (Bland-Altman analysis). Multi-segment image reconstruction improves temporal resolution compared to the standard ACV algorithm, but this does not result in a benefit for determination of LV volume and function.

Adult↗

PubMed1992

An endoscopic retrograde cholangiopancreatography (ERCP)-based algorithm for the management of pancreatic pseudocysts.

In the treatment of pancreatic pseudocysts, percutaneous and endoscopic drainage have, in certain cases, become alternatives to surgery. However, each treatment modality carries risks of complications and recurrences that may be minimized by the appropriate allocation of therapy. This article proposes the use of an endoscopic retrograde cholangiopancreatography (ERCP)-based algorithm as a means to allocate pseudocyst therapy based on the findings of pancreatic duct obstruction or pseudocyst communication. To evaluate this algorithm, the records of a series of patients with pancreatic pseudocysts seen at Duke University Medical Center from 1984 to 1990 were reviewed. Of 102 patients, 73 had symptomatic pseudocysts that required treatment. Forty of the 69 elective interventions were preceded by ERCPs and retrospectively applied to the algorithm. The number of adverse outcomes (treatment failures + complications) of the group that followed the algorithm was 3 of 26 (12%), while the number of adverse outcomes of the group that did not follow the algorithm was 6 of 14 (43%) (p less than 0.04 by Fisher's exact test). These two subgroups were similar in all other characteristics examined. Therefore, this ERCP-based algorithm may be used to allocate pseudocyst treatment; however, a prospective trial is necessary to prove its efficacy.

Algorithms↗

PubMed1991

A parallelizing algorithm for computing solutions to arbitrarily branched cable neuron models.

An algorithm for the solution of branching one-dimensional cable neuron models is presented. The algorithm is based on solving the finite-difference approximations to a cable or compartmental model of a neuron with a time implicit integration scheme. The algorithm solves the linear system of equations that must be solved at each time step with implicit algorithms via an "exact domain decomposition." This domain decomposition allows the solution of the unbranched and branching regions of the neuron to be done separately and permits a wide variety of possible implementations on parallel computers. Similarly, the separation of the straight and branched regions allows the solution of these two problems to be accomplished with linear system algorithms optimized for each class of problems. In contrast to other widely used methods (Hines, M. (1984) Int. J. Biomed. Comput., 15: 69-75), this algorithm can be used with arbitrary branching geometries, even those which contain closed loops.

Algorithms↗

PubMed1993

Algorithms for detection and measurement of spontaneous events.

The development of the personal computer and its mass storage capabilities has enabled long-term digitization of voltage records at high sampling rates. This paper presents a program that employs algorithms to analyze a sampled record for spontaneously occurring events. A detection algorithm employs amplitude and temporal parameters to identify the onsets of these events. Other algorithms then characterize size and shape features of these events. Examples of the results of these algorithms are given for intracellularly recorded excitatory postsynaptic potentials (EPSPs). These algorithms permit rapid and accurate quantitation of tens of thousands of events that may occur over many minutes. It is suggested that this set of algorithms may be applied to biological events other than synaptic potentials.

Algorithms↗

PubMed1994

An algorithm to detect low incidence arrhythmic events in electrocardiographic records from ambulatory patients.

An algorithm was devised to detect low incidence arrhythmic events in electrocardiograms obtained during ambulatory monitoring. The algorithm incorporated baseline correction and R wave detection. The RR interval was used to identify tachycardia, bradycardia, and premature ventricular beats. Only a few beats before and after the arrhythmic event were stored. The software was evaluated on a prototype hardware system which consisted of an Intel 86/30 single board computer with a suitable analog pre-processor and an analog to digital converter. The algorithm was used to determine the incidence and type of arrhythmia in records from an ambulatory electrocardiogram (ECG) database and from a cardiac exercise laboratory. These results were compared to annotations on the records which were assumed to be correct. Standard criteria used previously to evaluate algorithms designed for arrhythmia detection were sensitivity, specificity, and diagnostic accuracy. Sensitivities ranging from 77 to 100%, specificities from 94 to 100%, and diagnostic accuracies from 92 to 100% were obtained on the different data sets. These results compare favourably with published results based on more elaborate algorithms. By circumventing the need to make a continuous record of the ECG, the algorithm could form the basis for a compact monitoring device for the detection of arrhythmic events which are so infrequent that standard 24-h Holter monitoring is insufficient.

Algorithms↗

PubMed1996

Implementation of OSPOP, an algorithm for the estimation of optimal sampling times in pharmacokinetics by the ED, EID and API criteria.

The most common approach to optimize the sampling schedule in parameter estimation experiments is the D-optimality criterion, which consists in maximizing the determinant of the Fisher information matrix (max det F). In order to incorporate prior parameter uncertainty in the optimal design, other criteria have been proposed: The ED = max E (det F), EID = min E (l/det F) and API = max E (log det F) criteria, where the expectation is with respect to the given prior distribution of the parameters. Previously described algorithm for the estimation of optimal sampling times according to these criteria are adaptive random search (ARS), a robust and global but slow optimizer for API, and stochastic gradient (SG), a fast but local optimizer for ED and EID. We implemented an algorithm named OSPOP 1.0, based on non-adaptive random search (RS) followed by stochastic gradient to determine optimal sampling times for parameter estimation in various pharmacokinetic models according to ED, EID and API criteria. Prior distributions are allowed to be uniform, normal or lognormal. This algorithm combines the robustness of RS and the speediness of SG (convergence is obtained in a few minutes on a microcomputer). The results of the SG algorithm have been compared to those described in the literature using the ARS algorithm on a one compartment model with first- order absorption and were very similar. Also, the CPU time needed by SG and ARS algorithms were compared and the former proved to be much faster. Then, it has been applied to a five parameters stochastic model with zero-order absorption rate and Weibull-distributed residence times which was shown to describe adequately the kinetics of metacycline in humans. Population pharmacokinetic parameters of metacycline were estimated from a six subject pilot study, by the iterative two-staged method, using ADAPT II repeatedly. Optimal sampling times were determined with each criterion (ED, EID, API) with a multivariate normal prior parameter distribution. Six to seven distinct sampling times could be estimated. Higher numbers of samples revealed coalescing of design points.

Algorithms↗

PubMed1994

Evolutionary algorithms and a fractal inverse problem.

Over the past 30 years, algorithms that model natural evolution have generated robust search methods. These so-called evolutionary algorithms have been successfully applied to a wide range of problems. This paper discusses two types of evolutionary algorithms and their application to a problem in shape representation. Genetic algorithms and evolutionary programming, although both based on evolutionary principles, each place different emphasis on what drives the evolutionary process. While genetic algorithms rely on mimicking specific genotypic transformations, evolutionary programming emphasizes phenotypic adaptation. Results presented show the success of evolutionary programming in solving an example of a fractal inverse problem, but indicate that a genetic algorithm is not as successful. Reasons for this disparity are discussed.

Algorithms↗

PubMed1995

An iterative filtered backprojection inverse treatment planning algorithm for tomotherapy.

PURPOSE: An inverse treatment planning algorithm for tomotherapy is described. METHODS AND MATERIALS: The algorithm iteratively computes a set of nonnegative beam intensity profiles that minimizes the least-square residual dose defined in the target and selected normal tissue regions of interest. At each iteration the residual dose distribution is transformed into a set of residual beam profiles using an inversion method derived from filtered backprojection image reconstruction theory. These "residual" profiles are used to correct the current beam profile estimates resulting in new profile estimates. Adaptive filtering is incorporated into the inversion model so that the gross structure of the dose distribution is optimized during initial iterations of the algorithm, and the fine structure corresponding to edges is obtained at later iterations. A three dimensional, kernel based, convolutions/superposition dose model is used to compute dose during each iteration. RESULTS: Two clinically relevant treatment planning examples are presented illustrating the use of the algorithm for planning conformal radiotherapy of the breast and the prostate. Solutions are generally achieved in 10-20 iterations requiring about 20 h of CPU time using a midrange workstation. The majority of the calculation time is spent on the three-dimensional dose calculation. CONCLUSIONS: The inverse treatment planning algorithm is a useful research tool for exploring the potential of tomotherapy for conformal radiotherapy. Further work is needed to (a) achieve clinically acceptable computation times; (b) verify the algorithm using multileaf collimator technology; and (c) extend the method to biological objectives.

Algorithms↗

PubMedDate not supplied

SiMCAL 1 algorithm for analysis of gene expression data related to the phosphatidylserine receptor.

OBJECTIVE: SiMCAL 1 (simple multilevel clustering and linking, version 1) is a novel clustering algorithm for time-series microarray data, presented here with an application to a specific data set. The purpose of the algorithm is to present a complete feature set not found in either Jarvis-Patrick clustering, from which it is derived, or in other popular clustering methods such as hierarchical and k-means. The data concern the activity of the phosphatidylserine receptor (PSR) which is believed to be a crucial molecular switch in the mediation of inflammatory response in apoptosis and lysis. By analyzing the behavior of PSR-related genes in mouse macrophages, we hope to elucidate the mechanisms involved in this important biological process. METHODS AND MATERIALS: SiMCAL 1 is implemented in the Python programming language using the Numerical Python extensions, and the data are stored using the MySQL database management system. The data are derived from exposures of multiple Affymetrix mouse gene microarray chips to elevated levels of PSR antibody and control conditions. Code and data are available at (accessed: 17 January 2005). RESULTS: The algorithm meets its objectives: it is simple, in that it is computationally inexpensive; it is multilevel, in that it provides a small number of clearly defined hierarchical levels of clusters; and it offers linking between clusters at the same level in each hierarchy. Clustering and linking results indicate previously unknown co-regulation for genes expressing PGH synthase (COX2) and PGE2, appear to confirm increased production of proteins for clearance of apoptotic cells in the presence of PSR antibody, and correspond to other findings regarding the temporal relationship between PGE2 production and B cell proliferation and differentiation. These results are promising but should be taken as highly preliminary. CONCLUSION: Both the algorithm and its application to this problem show great potential for future development. We plan to improve and extend the SiMCAL family of algorithms, and to obtain new data so that the algorithm(s) may be further applied to this and other problems of interest.

Algorithms↗

PubMed2005

Evaluation of the DotMap algorithm for locating analytes of interest based on mass spectral similarity in data collected using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry.

Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC x GC-TOF-MS) is a highly selective technique ideal for the analysis of complex mixtures. The instrument yields an abundance of data, with complete mass spectral scans at every time point in the GC x GC separation space. The development and application of appropriate tools for data mining is essential in making sense of the wealth of information available. An algorithm for locating analytes of interest based on mass spectral similarity in GC x GC-TOF-MS data, called DotMap, has been previously reported and is rigorously evaluated herein. A thorough investigation into the performance characteristics of DotMap, including the performance near the limit of detection and dynamic range of the algorithm as well as the capacity of the algorithm to deal with peak overlap, is investigated using jet fuel as a complex sample matrix. For instance, the algorithm can successfully identify a spiked compound at the single microg/ml level in a jet fuel sample with an overlapping interferent. The performance of the DotMap algorithm in situations with very limited mass spectral selectivity, specifically in the evaluation of spectra from isomer compounds, as well as the ability to tune DotMap results to provide the location of a specific analyte or of a class of compounds is demonstrated. The DotMap algorithm is demonstrated to be a sensitive tool that is useful in the analysis of complex mixtures and which possesses the capacity to be easily "tuned" to discern the location of analytes of interest.

Algorithms↗

PubMed2004

Seizure detection: evaluation of the Reveal algorithm.

OBJECTIVE: The aim of this study is to evaluate an improved seizure detection algorithm and to compare with two other algorithms and human experts. METHODS: 672 seizures from 426 epilepsy patients were examined with the (new) Reveal algorithm which utilizes 3 methods, novel in their application to seizure detection: Matching Pursuit, small neural network-rules and a new connected-object hierarchical clustering algorithm. RESULTS: Reveal had a sensitivity of 76% with a false positive rate of 0.11/h. Two other algorithms (Sensa and CNet) were tested and had sensitivities of 35.4 and 48.2% and false positive rates of 0.11/h and 0.75/h, respectively. CONCLUSIONS: This study validates the Reveal algorithm, and shows it to compare favorably with other methods. SIGNIFICANCE: Improved seizure detection can improve patient care in both the epilepsy monitoring unit and the intensive care unit.

Adolescent↗

PubMed2004

An adaptive and iterative algorithm for refining multiple sequence alignment.

Multiple sequence alignment is a basic tool in computational genomics. The art of multiple sequence alignment is about placing gaps. This paper presents a heuristic algorithm that improves multiple protein sequences alignment iteratively. A consistency-based objective function is used to evaluate the candidate moves. During the iterative optimization, well-aligned regions can be detected and kept intact. Columns of gaps will be inserted to assist the algorithm to escape from local optimal alignments. The algorithm has been evaluated using the BAliBASE benchmark alignment database. Results show that the performance of the algorithm does not depend on initial or seed alignments much. Given a perfect consistency library, the algorithm is able to produce alignments that are close to the global optimum. We demonstrate that the algorithm is able to refine alignments produced by other software, including ClustalW, SAGA and T-COFFEE. The program is available upon request.

Algorithms↗

PubMedDate not supplied

Optimisation of the predictive ability of artificial neural network (ANN) models: a comparison of three ANN programs and four classes of training algorithm.

The purpose of this study was to determine whether artificial neural network (ANN) programs implementing different backpropagation algorithms and default settings are capable of generating equivalent highly predictive models. Three ANN packages were used: INForm, CAD/Chem and MATLAB. Twenty variants of gradient descent, conjugate gradient, quasi-Newton and Bayesian regularization algorithms were used to train networks containing a single hidden layer of 3-12 nodes. All INForm and CAD/Chem models trained satisfactorily for tensile strength, disintegration time and percentage dissolution at 15, 30, 45 and 60 min. Similarly, acceptable training was obtained for MATLAB models using Bayesian regularization. Training of MATLAB models with other algorithms was erratic. This effect was attributed to a tendency for the MATLAB implementation of the algorithms to attenuate training in local minima of the error surface. Predictive models for tablet capping and friability could not be generated. The most predictive models from each ANN package varied with respect to the optimum network architecture and training algorithm. No significant differences were found in the predictive ability of these models. It is concluded that comparable models are obtainable from different ANN programs provided that both the network architecture and training algorithm are optimised. A broad strategy for optimisation of the predictive ability of an ANN model is proposed.

Algorithms↗

PubMed2004

Atrial pacing for prevention of atrial fibrillation: assessment of simultaneously implemented algorithms.

AIMS: Several preliminary studies indicated that right atrial pacing could prevent atrial tachyarrhythmias (ATA). We sought to compare the safety and the efficacy of atrial-based pacing supplemented by dedicated combined algorithms with conventional atrial pacing in the prevention of ATA. METHODS: Fifty-five patients with a history of recurrent paroxysmal ATA implanted with a dual-chamber pacemaker were studied during two randomized cross-over pacing periods (conventional DDD and DDD with ATA prevention algorithms) of 6 months duration. The primary endpoint was the burden of ATA episodes recorded by the device mode switch algorithm. RESULTS: The cross-over analysis did not demonstrate any significant difference between the two pacing modes: 254+/-533 h of ATA during the control period versus 238+/-518 h during the ATA prevention period. Analysis of a subgroup of patients found that those with the lower percentage of ventricular pacing benefited from ATA prevention algorithms (120+/-182 h versus 225+/-350 h during the control period; P < 0.04). CONCLUSION: When compared with DDD pacing at 70 bpm, ATA prevention algorithms have not demonstrated significant efficacy. However, a subgroup of patients with preserved native AV conduction (low percentage of ventricular pacing) responded to ATA prevention algorithms.

Aged↗

PubMed2003

The use of calculated epicardial potentials improves significantly the sensitivity of a diagnostic algorithm in the detection of acute myocardial infarction.

Inverse electrocardiography can calculate epicardial potentials (EP) from body surface potentials (BSP) taking into account a thoracic volume conductor model (TVCM). Previous studies have shown that a tailored TVCM is superior to a general TVCM in calculating EP. However, construction of a tailored TVCM for a patient in an acute clinical setting is impractical. In this study we used a general TVCM in our EP calculations to determine whether this improves detection of acute myocardial infarction (AMI) using a diagnostic algorithm. BSP were derived from the 80-lead body surface map (BSM). Consecutive patients (n=379) with ischemic type chest pain were recruited. The BSM and a 12-lead electrocardiogram (ECG) were recorded at initial presentation and creatine kinase (CK) and/or CK-MB were measured initially, 12 and 24 hours postsymptom onset. A physician interpreted the 12-lead electrocardiogram and documented ST elevation if present. AMI was defined by the World Health Organization (WHO) criteria. The diagnostic algorithm result for each patient using BSP and calculated EP were documented. AMI occurred in 171 patients. The diagnostic algorithm using BSP identified 106 of these as ST elevation AMI (STEMI) (sensitivity 62%, specificity 80%). The same algorithm using EP identified 133 as STEMI (sensitivity 78%, specificity 80%). Calculated EP improved the algorithm's diagnostic sensitivity by a factor of 1.25 (P<.001) with no significant difference in specificity. Calculated EP using a general TVCM significantly improves the sensitivity of a diagnostic algorithm based on BSP in detection of AMI with no significant loss in specificity.

Algorithms↗

PubMed2005

Adaptive algorithms for first principal eigenvector computation.

The paper presents a unified framework to derive and analyze 10 different adaptive algorithms, some well-known, to compute the first principal eigenvector of the correlation matrix of a random vector sequence. Since adaptive principal eigenvector algorithms have originated from a diverse set of disciplines, including ad hoc methods, it is necessary to examine them in a unified framework. In a common framework consisting of five steps, we analyze the derivation, convergence, and rate results for many well-known algorithms as well as two new adaptive algorithms. In the process, we offer fresh perspectives on the known algorithms, and derive new results for others. The common framework also allows us to comparatively study the 10 algorithms. Finally, we show experimental results to support our analyses.

Algorithms↗

PubMed2004

Dosimetric verification of a commercial collapsed cone algorithm in simulated clinical situations.

BACKGROUND AND PURPOSE: This work reports a detailed study carried out in two UK radiotherapy centres of the dosimetric accuracy of the collapsed cone algorithm of a commercial treatment planning system (Helax-TMS) in simulated clinical situations. MATERIALS AND METHODS: Initially the accuracy of the collapsed cone algorithm in homogeneous media is evaluated for an extensive set of simple and complex fields. Water, lung and bone substitute epoxy resin material were then used to assess the algorithm in inhomogeneous media and compare its accuracy with the pencil beam algorithm currently in clinical use. Finally a semi-anatomic phantom and an anthropomorphic phantom were employed to assess the dosimetric accuracy using simulated clinical set ups. Thermoluminescence dosimeter (TLD) measurements were made with the anthropomorphic phantom and ionisation chambers otherwise. Nominal 4, 6 and 15 MV photon beams were studied. RESULTS: For most homogeneous cases agreement between measured and calculated dose is within +/-2% or +/-2 mm. In cases with heterogeneities and simulated clinical situations it is observed that the accuracy is also generally within +/-2% or +/-2 mm. Specific instances where the difference between measured and calculated values exceed this are highlighted. CONCLUSIONS: It can be concluded that in clinical treatment planning situations where lung is present the collapsed cone algorithm should be considered in preference to pencil beam algorithms normally used but that there may still be some discrepancy between calculations and measurement.

Algorithms↗

PubMed2005

Management of septic shock with a norepinephrine-based haemodynamic algorithm.

UNLABELLED: Management of septic shock (SS) with a norepinephrine (noradrenaline)-based haemodynamic algorithm. INTRODUCTION: The choice of the best vasopressor for haemodynamic management of septic shock is controversial. Nevertheless, very few studies have been focused on evaluating different management algorithms. The aim of this study was to evaluate the performance of a norepinephrine (NE)-based management protocol. Experience with NE as the initial vasopressor, even if not comparative, could bring relevant data for planning future trails. We also wanted to evaluate the compliance of critical care physicians and nurses with haemodynamic management protocol. PATIENTS AND METHOD: A norepinephrine-based algorithm for the management of septic shock that commands different sequential interventions according to its requirements, was applied prospectively to 100 consecutive septic shock patients. RESULTS: Norepinephrine was used as the first vasoactive drug in all patients with a maximum dose of 0.31+/-0.3 microg kg(-1)min(-1) and an ICU mortality of 33%. Physicians applied correctly all the steps of the algorithm in 92% of the patients. Applying the algorithm, avoided the use of pulmonary artery catheter in 31 patients and led to use of lower doses of vasoactive agents than in many other clinical experiences. CONCLUSION: In conclusion, our data support extended use of an algorithm based on norepinephrine for treating septic shock patients. This is the first clinical study that uses NE as the initial vasopressor drug systematically, and although not comparative, the mortality rates adjusted to APACHE II, are comparable to other studies. It also gives support for future clinical trials comparing norepinephrine with dopamine in this setting.

Aged↗