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PubMed1998

AmbiPack: a systematic algorithm for packing of macromolecular structures with ambiguous distance constraints.

The determination of structures of multimers presents interesting new challenges. The structure(s) of the individual monomers must be found and the transformations to produce the packing interfaces must be described. A substantial difficulty results from ambiguities in assigning intermolecular distance measurements (from nuclear magnetic resonance, for example) to particular intermolecular interfaces in the structure. Here we present a rapid and efficient method to solve the packing and the assignment problems simultaneously given rigid monomer structures and (potentially ambiguous) intermolecular distance measurements. A promising application of this algorithm is to couple it with a monomer searching protocol such that each monomer structure consistent with intramolecular constraints can be subsequently input to the current algorithm to check whether it is consistent with (potentially ambiguous) intermolecular constraints. The algorithm AmbiPack uses a hierarchical division of the search space and the branch-and-bound algorithm to eliminate infeasible regions of the space. Local search methods are then focused on the remaining space. The algorithm generally runs faster as more constraints are included because more regions of the search space can be eliminated. This is not the case for other methods, for which additional constraints increase the complexity of the search space. The algorithm presented is guaranteed to find all solutions to a predetermined resolution. This resolution can be chosen arbitrarily to produce outputs at various level of detail. Illustrative applications are presented for the P22 tailspike protein (a trimer) and portions of beta-amyloid (an ordered aggregate).

Algorithms↗

PubMed2006

The BeLPT: algorithms and implications.

BACKGROUND: The beryllium lymphocyte proliferation test (BeLPT) is used to identify persons with beryllium sensitization. The variability of laboratory results and lack of a "gold standard" have led to questions about the test's performance. Fortunately, a recently published study has credibly estimated standard epidemiologic parameters for the BeLPT. METHODS: Information from this recent study was used to assess the performance of two common algorithms for BeLPT testing. Standard epidemiologic parameters were determined for two common algorithms and then compared. RESULTS: One of the two algorithms was more sensitive than the other (86% vs. 66%). The specificity of both algorithms (99.8% or greater) was high. At an estimated 2% prevalence, the positive predictive value of both algorithms for beryllium sensitization remained high (90% or higher). CONCLUSIONS: A priori characterization of the testing algorithm under consideration can enhance public health decision-making.

Algorithms↗

PubMed1994

Brief communication: bone remodeling rates: a test of an algorithm for estimating missing osteons.

Frost (1987a) proposed an algorithm for estimating the number of missing osteons that correspond to observed osteon population densities (OPD). Such an algorithm should allow more accurate estimates of bone remodeling rates for skeletal remains for which in vivo labeling is not possible. In order to validate the algorithm, it was tested on an autopsy sample of 44 ribs. Estimates of activation frequency (mu RC) and bone remodeling rate (Vf,r,t) using the new algorithm are in reasonable agreement with age-matched tetracycline-based values. Although mean values for activation frequencies (mu RC) and bone formation rate (Vf,r,t) generated by the algorithm were generally lower, they fell below 1 standard error for only an age category that included all ages above the 5th decade. It is now appropriate to apply the algorithm to archaeological skeletal remains.

Age Determination by Skeleton↗

PubMed1995

An evaluation of numerical integration algorithms for the estimation of the area under the curve (AUC) in pharmacokinetic studies.

Six numerical integration algorithms based on linear and log trapezoidal methods as well as four cubic-spline methods were proposed for estimation of area under the curve (AUC). These six different algorithms were implemented using IMSL/IDL command language and evaluated using data simulated under five different dosing conditions and two different sampling conditions. Comparisons between AUC estimations using these six different algorithms and the theoretical results were made in terms of both overall AUC values and the superimposability of the concentration-time profiles. In well designed studies with ample data points, the algorithm based on IMSL/IDL function CSSHAPE with concavity preservation gave the best performance. In contrast, when the frequency of blood collection was limited, the algorithm based on the log trapezoidal rule proved to be stable with reasonable accuracy, and is recommended as the practical method for numerical interpolation and integration in pharmacokinetic studies. Algorithms based on the combination of the log trapezoidal rule and cubic-spline methods using IMSL/IDL function CSSHAPE can be developed to enhance overall performance.

Algorithms↗

PubMedDate not supplied

The sampling properties of some distance geometry algorithms applied to unconstrained polypeptide chains: a study of 1830 independently computed conformations.

In this paper we study the statistical geometry of ensembles of poly (L-alanine) conformations computed by several different distance geometry algorithms. Since basic theory only permits us to predict the statistical properties of such ensembles a priori when the distance constraints have a very simple form, the only constraints used for these calculations are those necessary to obtain reasonable bond lengths and angles, together with a lack of short- and long-range atomic overlaps. The geometric properties studied include the squared end-to-end distance and radius of gyration of the computed conformations, in addition to the usual rms coordinate and phi/psi angle deviations among these conformations. The distance geometry algorithms evaluated include several variations of the well-known embed algorithm, together with optimizations of the torsion angles using the ellipsoid and variable target function algorithms. The conclusions may be summarized as follows: First, the distribution with which the trial distances are chosen in most implementations of the embed algorithm is not appropriate when no long-range upper bounds on the distances are present, because it leads to unjustifiably expanded conformations. Second, chosing the trial distances independently of one another leads to a lack of variation in the degree of expansion, which in turn produces a relatively low rms square coordinate difference among the members of the ensemble. Third, when short-range steric constraints are present, torsion angle optimizations that start from conformations obtained by choosing their phi/psi angles randomly with a uniform distribution between -180 degrees and +180 degrees do not converge to conformations whose angles are uniformly distributed over the sterically allowed regions of the phi/psi plane. Finally, in an appendix we show how the sampling obtained with the embed algorithm can be substantially improved upon by the proper application of existing methodology.

Algorithms↗

PubMed2002

Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?

Independent component analysis (ICA) has been successfully employed to decompose functional MRI (fMRI) time-series into sets of activation maps and associated time-courses. Several ICA algorithms have been proposed in the neural network literature. Applied to fMRI, these algorithms might lead to different spatial or temporal readouts of brain activation. We compared the two ICA algorithms that have been used so far for spatial ICA (sICA) of fMRI time-series: the Infomax (Bell and Sejnowski [1995]: Neural Comput 7:1004-1034) and the Fixed-Point (Hyvärinen [1999]: Adv Neural Inf Proc Syst 10:273-279) algorithms. We evaluated the Infomax- and Fixed Point-based sICA decompositions of simulated motor, and real motor and visual activation fMRI time-series using an ensemble of measures. Log-likelihood (McKeown et al. [1998]: Hum Brain Mapp 6:160-188) was used as a measure of how significantly the estimated independent sources fit the statistical structure of the data; receiver operating characteristics (ROC) and linear correlation analyses were used to evaluate the algorithms' accuracy of estimating the spatial layout and the temporal dynamics of simulated and real activations; cluster sizing calculations and an estimation of a residual gaussian noise term within the components were used to examine the anatomic structure of ICA components and for the assessment of noise reduction capabilities. Whereas both algorithms produced highly accurate results, the Fixed-Point outperformed the Infomax in terms of spatial and temporal accuracy as long as inferential statistics were employed as benchmarks. Conversely, the Infomax sICA was superior in terms of global estimation of the ICA model and noise reduction capabilities. Because of its adaptive nature, the Infomax approach appears to be better suited to investigate activation phenomena that are not predictable or adequately modelled by inferential techniques.

Adult↗

PubMedDate not supplied

Using algorithms in rehabilitation nursing: an educational strategy.

The purpose of this article is to describe the use of algorithms in the specialty practice of rehabilitation nursing. Algorithms are particularly useful for the nurse who is new to rehabilitation because they can offer guidance in some important aspects of clinical decision making. In this article, the authors include information on the historical uses of algorithms, the benefits of using algorithms, and the ways in which algorithms are developed. Examples are also included, and suggestions for further development of algorithms in rehabilitation nursing are proposed.

Algorithms↗

PubMedDate not supplied

Correspondence of closest gradient voxels--a robust registration algorithm.

A robust, automatic volume registration algorithm based on intensity gradients is presented. This algorithm can successfully perform registrations under conditions of unrelated intervolume voxel intensities, significant object displacements, and/or significant amounts of missing data. It also allows the user to visualize the registration convergence, clearly illustrating any source of registration errors. This algorithm consists of a matching algorithm based on iteratively finding the correspondence of the closest voxels containing a high three-dimensional intensity gradient magnitude. This algorithm was tested by registering T2-weighted MR volumes that had undergone varying displacement transformations to simultaneously acquired proton-density volumes. These transformations involved rotations of up to 25 degrees followed by translations of up to 25 mm along the axis of rotation. For all registrations, the mean registration error was less than one-fifth of a voxel and the mean registration time was less than 30 minutes. In conclusion, this algorithm is shown to be a powerful method of sequence-independent MR volume registration that is simple to both use and understand.

Algorithms↗

PubMed2006

Quantitative myocardial infarction on delayed enhancement MRI. Part I: Animal validation of an automated feature analysis and combined thresholding infarct sizing algorithm.

PURPOSE: To develop a computer algorithm to measure myocardial infarct size in gadolinium-enhanced magnetic resonance (MR) imaging and to validate this method using a canine histopathological reference. MATERIALS AND METHODS: Delayed enhancement MR was performed in 11 dogs with myocardial infarction (MI) determined by triphenyltetrazolium chloride (TTC). Infarct size on in vivo and ex vivo images was measured by a computer algorithm based on automated feature analysis and combined thresholding (FACT). For comparison, infarct size by human manual contouring and simple intensity thresholding (based on two standard deviation [2SD] and full width at half maximum [FWHM]) were studied. RESULTS: Both in vivo and ex vivo MR infarct size measured by the FACT algorithm correlated well with TTC (R = 0.95-0.97) and showed no significant bias on Bland Altman analysis (P = not significant). Despite similar correlations (R = 0.91-0.97), human manual contouring overestimated in vivo MR infarct size by 5.4% of the left ventricular (LV) area (equivalent to 55.1% of the MI area) vs. TTC (P < 0.001). Infarct size measured by simple intensity thresholdings was less accurate than the proposed algorithm (P < 0.001 and P = 0.007). CONCLUSION: The FACT algorithm accurately measured MI size on delayed enhancement MR imaging in vivo and ex vivo. The FACT algorithm was also more accurate than human manual contouring and simple intensity thresholding approaches.

Algorithms↗

PubMed2003

Deconvolution algorithm based on automatic cutoff frequency selection for EPR imaging.

The large line-width associated with electron paramagnetic resonance imaging (EPRI) requires effective algorithms to deconvolve the true spatial profiles of spins from the measured projection data. The commonly used Fourier transform (FT) deconvolution algorithm is easy to implement but suffers from the division-by-zero problem. As a result, a couple of parameters are used to control the deconvolution performance. However, this is inconvenient and the deconvolution results are subject to the experience of the operators. In the present work we examined FT deconvolution for EPRI, and proposed an automatic algorithm to determine the cutoff frequency by calculating the piecewise variance of the division result of the Fourier amplitude spectra. The deconvolution algorithm and the filtered back-projection image reconstruction algorithm were implemented and validated using 3D phantom and in vivo imaging data. It was clearly observed that the image resolution improved after deconvolution with the proposed algorithm.

Algorithms↗

PubMed1989

An automated iterative algorithm for the quantitative analysis of in vivo spectra based on the simplex optimization method.

The success in utilizing in vivo NMR to identify and/or monitor metabolic abnormalities will be determined in large part on the reliability with which the spectral parameters of the metabolites present can be measured. For these reasons it is clear that there is a need for the development of algorithms with which to obtain quantitatively reliable estimates of the spectral parameters of the peaks present. In this report we describe an adaptation of the simplex algorithm which we have found useful in fitting in vivo spectral data in the frequency domain. This simplex algorithm was implemented on an IBM-PC AT compatible computer. We evaluated the simplex algorithm on three representative kinds of spectral data: a simulated spectrum, 31P spectrum of normal calf muscle, and the 31P spectrum of a pediatric patient with a brain tumor. In each case we generated a set of spectra by adding varying amounts of noise. On the basis of our simulations and the two examples discussed, we conclude that the simplex method generates parameters which are reliable estimates of the areas of the peaks present when the signal-to-noise is above 8:1 for phosphocreatine. We found that the speed of convergence of the algorithm was improved by overestimating the linewidths of the peaks present. We also found that the method converged more rapidly in the presence of a moderate amount of noise. We conclude that the algorithm described here can provide a robust method with which to analyze in vivo spectra in a quantitative manner. Because the method requires little user intervention, it lends itself to implementation in a semi-, or fully, automated fashion.

Algorithms↗

PubMed2005

Causality assessment of adverse drug reactions: comparison of the results obtained from published decisional algorithms and from the evaluations of an expert panel.

PURPOSE: To compare the results of causality assessments of reported adverse drug reactions (ADR's) obtained from decisional algorithms with those obtained from an expert panel using the WHO global introspection method (GI) and to further evaluate the influence of confounding variables on algorithms ability in assessing causality. METHOD: Two hundred sequentially reported ADR's were included in this study. An independent researcher used algorithms, while an expert panel assessed the same reports using the GI, both aimed at evaluating causality. Reports were divided into three groups according to the presence, absence or lack of information on confounding variables. RESULTS: For the total sample, observed agreements between decisional algorithms compared with GI varied from 21% to 56%, average of 47%. When confounding variables were taken into account, agreements varied between 41% and 69%, average of 58%; 8% and 65%, average of 46% and 15% and 53%, average of 42% accordingly to the absence, lack of information or presence of confounding variables, respectively. The extend of reproducibility beyond chance was low for the total sample (average Kappa = 0.26) and within the groups considered. CONCLUSION: The overall observed agreement between algorithm and GI was moderate although poorly different from chance, confounding variables being a shortcoming of algorithms ability in assessing causality.

Adverse Drug Reaction Reporting Systems↗

PubMed1995

An innovative dicrotic notch detection algorithm which combines rule-based logic with digital signal processing techniques.

Automated, real-time localization of the dicrotic notch, a component of the arterial pressure waveform, represents a deceptively complex problem in computerized biomedical signal processing. The high-frequency nature of the notch can make it difficult to distinguish from artifactual noise or from other high-frequency physiological components of the waveform. In addition, the contour of the notch varies with vascular status and with propagation through arterial beds, requiring any detection algorithm to recognize various possible notch conformations. Finally, location of the notch along the waveform may vary widely depending on other hemodynamic variables, further complicating detection algorithms. We have reviewed various published algorithms and have implemented a number of them to determine the strengths and shortcomings of each. We then developed a reliable and accurate hybrid algorithm which utilizes the strengths of the various algorithmic approaches reviewed; after analyzing the waveform, the algorithm selects the most appropriate method for accurate notch localization based on a series of waveform features. The application of rule-based logic represents a relatively unique approach to digital signal processing.

Algorithms↗

PubMed2000

A decentralized multichannel length transformation algorithm and its parallel implementation for real-time ECG monitoring.

Multichannel algorithms have been developed for more accurate analysis of electrocardiograms (ECGs). Their benefit is the ability to use the information contained in all simultaneously acquired channels. In this paper we present a multichannel version of a nonsyntactic algorithm, based on length transformation. The proposed algorithm uses a decentralized schema for combining the results derived from each individual lead, instead of a global/centralized one (a spatial vector approach). Its performance was evaluated using the CSE database and real ECGs acquired by a 12-lead cardiograph. The results are also compared with previous-single-channel and multichannel-versions of the algorithm, showing a better performance. Since a multichannel algorithm is always a time-consuming task, it is rarely used in real-time monitoring systems. Motivated by this observation, we designed a parallel implementation of the proposed algorithm and tested its ability to be used in such systems.

Algorithms↗

PubMed1996

Multiple sequence information for threading algorithms.

Threading algorithms attempt to solve the inverse protein folding problem: given a group of structures and a sequence, identify the structure that is most compatible with this sequence. A recent study of this class of algorithms by S. J. Wodak and colleagues suggests that while threading algorithms are capable of recognizing many folding motifs, their performance in truly blind predictions is disappointing, and the underlying alignments upon which the selections are based are frequently errant. To help overcome this problem we have developed a Test of Optimal Mutagenesis algorithm (TOM) that exploits information inherent in the variation between several homologues in a multiple sequence alignment. This information is used to help select the correct structural motif for the sequence from a database of known structures. A total of 305 high-resolution structures were selected to represent the set of known folds; 56 proteins were chosen that had at least one close structural match in this set. To test TOM, we attempted to determine which of the 305 folds was a match to each of the 56 protein sequences. TOM correctly predicts a close structural match for 45% of these proteins. THREADER, an algorithm chosen as a literature standard, correctly matched 20% of the test set. By comparing the performance of TOM, THREADER, and TOM NOVAR (a version of TOM without variability information), we conclude that the tendency of an amino acid to be buried or exposed is the dominant determinant of the success of threading algorithms. In addition, the structural alignments produced by TOM suggest that the exact alignment of just 30 to 50% of the residues in a sequence with the correct fold is necessary to select it as the highest scoring match in a set of folds.

Algorithms↗

PubMed1992

A motion correction algorithm for an image realignment programme useful for sequential radionuclide renography.

The correction of organ movements in sequential radionuclide renography was done using an iterative algorithm that, by means of a set of rectangular regions of interest (ROIs), did not require any anatomical marker or manual elaboration of frames. The realignment programme here proposed is quite independent of the spatial and temporal distribution of activity and analyses the rotational movement in a simplified but reliable way. The position of the object inside a frame is evaluated by choosing the best ROI in a set of ROIs shifted 1 pixel around the central one. Statistical tests have to be ful-filled by the algorithm in order to activate the realignment procedure. Validation of the algorithm was done for different acquisition set-ups and organ movements. Results, summarized in Table 1, show that in about 90% of the simulated experiments the algorithm is able to correct the movements of the object with a maximum error less or equal to 1 pixel limit. The usefulness of the realignment programme was demonstrated with sequential radionuclide renography as a typical clinical application. The algorithm-corrected curves of a 1-year-old patient were completely different from those obtained without a motion correction procedure. The algorithm may be applicable also to other types of scintigraphic examinations, besides functional imaging in which the realignment of frames of the dynamic sequence was an intrinsic demand.

Algorithms↗

PubMed1994

An evaluation of the accelerated expectation maximization algorithms for single-photon emission tomography image reconstruction.

We previously reported that brain single-photon emission tomography (SPET) images could be improved by using an attenuation coefficient map constructed with transmission data and the iterative expectation maximization (EM) algorithm. However, the conventional EM algorithm (CEM) typically requires 30-80 iterations to provide acceptable results, limiting its clinical applicability. Several methods have been proposed to accelerate the EM algorithm. The purpose of this study was to search for a practical method for accelerating the EM algorithm. The methods investigated here include the accelerated EM algorithm (ACEM) using additive correction, ACEM using multiplicative correction, and Tanaka's filtered iterative reconstruction method (FIR). These methods were assessed by simulated SPET studies of a phantom incorporating nonuniform attenuation and by reference to clinical brain SPET data. In the simulation studies, the above methods were evaluated by using three parameters (root mean square error, log likelihood value, and contrast recovery coefficient); the results showed that FIR had an advantage over other methods in terms of all parameters. The results obtained using the clinical data demonstrated that FIR could reconstruct acceptable images in only five iterations. These results show that FIR offers significant advantages over CEM or other ACEMs, indicating that FIR can make the EM algorithm practical for clinical use in SPET.

Adult↗

PubMed1995

Classification-algorithm evaluation: five performance measures based on confusion matrices.

OBJECTIVE: The objective of this paper is to introduce, explain, and extend methods for comparing the performance of classification algorithms using error tallies obtained on properly sized, populated, and labeled data sets. METHODS: Two distinct contexts of classification are defined, involving "objects-by-inspection" and "objects-by-segmentation." In the former context, the total number of objects to be classified is unambiguously and self-evidently defined. In the latter, there is troublesome ambiguity. All five of the measures of performance here considered are based on confusion matrices, tables of counts revealing the extent of an algorithm's "confusion" regarding the true classifications. A proper measure of classification-algorithm performance must meet four requirements. A proper measure should obey six additional constraints. RESULTS: Four traditional measures of performance are critiqued in terms of the requirements and constraints. Each measure meets the requirements, but fails to obey at least one of the constraints. A nontraditional measure of algorithm performance, the normalized mutual information (NMI), is therefore introduced. Based on the NMI, methods for comparing algorithm performance using confusion matrices are devised. CONCLUSIONS: The five performance measures lead to similar inferences when comparing a trio of QRS-detection algorithms using a large data set. The modified NMI is preferred, however, because it obeys each of the constraints and is the most conservative measure of performance.

Algorithms↗