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PubMed2001

A simple algorithm for identifying negated findings and diseases in discharge summaries.

Narrative reports in medical records contain a wealth of information that may augment structured data for managing patient information and predicting trends in diseases. Pertinent negatives are evident in text but are not usually indexed in structured databases. The objective of the study reported here was to test a simple algorithm for determining whether a finding or disease mentioned within narrative medical reports is present or absent. We developed a simple regular expression algorithm called NegEx that implements several phrases indicating negation, filters out sentences containing phrases that falsely appear to be negation phrases, and limits the scope of the negation phrases. We compared NegEx against a baseline algorithm that has a limited set of negation phrases and a simpler notion of scope. In a test of 1235 findings and diseases in 1000 sentences taken from discharge summaries indexed by physicians, NegEx had a specificity of 94.5% (versus 85.3% for the baseline), a positive predictive value of 84.5% (versus 68.4% for the baseline) while maintaining a reasonable sensitivity of 77.8% (versus 88.3% for the baseline). We conclude that with little implementation effort a simple regular expression algorithm for determining whether a finding or disease is absent can identify a large portion of the pertinent negatives from discharge summaries.

Algorithms↗

PubMed2000

Trading accuracy for speed: A quantitative comparison of search algorithms in protein sequence design.

Finding the minimum energy amino acid side-chain conformation is a fundamental problem in both homology modeling and protein design. To address this issue, numerous computational algorithms have been proposed. However, there have been few quantitative comparisons between methods and there is very little general understanding of the types of problems that are appropriate for each algorithm. Here, we study four common search techniques: Monte Carlo (MC) and Monte Carlo plus quench (MCQ); genetic algorithms (GA); self-consistent mean field (SCMF); and dead-end elimination (DEE). Both SCMF and DEE are deterministic, and if DEE converges, it is guaranteed that its solution is the global minimum energy conformation (GMEC). This provides a means to compare the accuracy of SCMF and the stochastic methods. For the side-chain placement calculations, we find that DEE rapidly converges to the GMEC in all the test cases. The other algorithms converge on significantly incorrect solutions; the average fraction of incorrect rotamers for SCMF is 0.12, GA 0.09, and MCQ 0.05. For the protein design calculations, design positions are progressively added to the side-chain placement calculation until the time required for DEE diverges sharply. As the complexity of the problem increases, the accuracy of each method is determined so that the results can be extrapolated into the region where DEE is no longer tractable. We find that both SCMF and MCQ perform reasonably well on core calculations (fraction amino acids incorrect is SCMF 0.07, MCQ 0.04), but fail considerably on the boundary (SCMF 0.28, MCQ 0.32) and surface calculations (SCMF 0.37, MCQ 0.44).

Algorithms↗

PubMed1999

A new algorithm for NMR spectral normalization.

There is increasing use of high-resolution NMR spectroscopy to examine variations in cell metabolism and/or structure in response to numerous physical, chemical, and biological agents. In these types of studies, in order to obtain relative quantitative information, a comparison between signal intensities of control samples and treated or exposed ones is often conducted. The methods thus far developed for this purpose are not directly related to the overall intrinsic properties of the samples, but rather to the addition of external substances of known concentrations or to indirect measurement of internal substances. In this paper, a new method for quantitatively comparing the spectra of cell samples is presented. It depends on a normalization algorithm which takes into consideration all cell metabolites present in the sample. In particular, the algorithm is based on maximizing, by an opportune sign variable measure, the spectral region in which the two spectra are superimposed. The algorithm was tested by Monte Carlo simulations as well as experimentally by comparing two samples of known contents with the new method and with an older method using a standard. At the end, the algorithm was applied to real spectra of cell samples to show how it could be used to obtain qualitative and quantitative biological information.

Algorithms↗

PubMed2002

A new time-domain frequency-selective quantification algorithm.

In this paper a new time-domain frequency-selective quantification algorithm is presented. Frequency-selective quantification refers to a method that analyzes spectral components in a selected frequency region, ignoring all the other components outside. The algorithm, referred to as MeFreS (Metropolis Frequency-Selective), is based on rank minimization of an opportune Hankel matrix. The minimization procedure is satisfied by the down-hill simplex method, implemented with the simulated annealing method. MeFreS does not use any preprocessing step or filter to suppress nuisance peaks, but the signal model function is directly fitted. In this manner, neither inherent signal distortions nor estimation biases to be corrected occur. The algorithm was tested with Monte Carlo simulations. A comparison with VARPRO and AMARESw algorithms was carried out. Finally, two samples of known content from NMR data were quantified.

Algorithms↗

PubMedDate not supplied

The effect of overabundant projection directions on 3D reconstruction algorithms.

The experimental process of collecting images from macromolecules in an electron microscope is such that it does not allow for prior specification of the angular distribution of the projection images. As a consequence, an uneven distribution of projection directions may occur. Concerns have been raised recently about the behavior of 3D reconstruction algorithms for the case of unevenly distributed projections. It has been illustrated on experimental data that in the case of a heavily uneven distribution of projection directions some algorithms tend to elongate the reconstructed volumes along the overloaded direction so much as to make a quantitative biological analysis impossible. In answer to these concerns we have developed a strategy for quantitative comparison and optimization of 3D reconstruction algorithms. We apply this strategy to quantitatively analyze algebraic reconstruction techniques (ART) with blobs, simultaneous iterative reconstruction techniques (SIRT) with voxels, and weighted backprojection (WBP). We show that the elongation artifacts that had been previously reported can be strongly reduced. With our specific choices for the free parameters of the three algorithms, WBP reconstructions tend to be inferior to those obtained with either SIRT or ART and the results obtained with ART are comparable to those with SIRT, but at a very small fraction of the computational cost of SIRT.

Algorithms↗

PubMed1993

A fast algorithm for the optimal alignment of three strings.

Ukkonen's (pair-wise) string alignment technique is extended to the problem of finding an optimal alignment for three strings. The resulting algorithm has worst-case time-complexity O(nd2) and space-complexity O(d3), where the string lengths are ñ and d is the three-way edit-distance based on tree-costs. In practice, the algorithm usually runs in O(n + d3) time. The algorithm is particularly fast when the strings are similar, in which case, d << n. Three-way alignment is an important special case in string alignment. Each internal node in an unrooted, binary evolutionary-tree has three neighbours. The algorithm presented can be used as an iterative step in a heuristic multiple-alignment program for more than three strings.

Algorithms↗

PubMed1995

An APL-programmed genetic algorithm for the prediction of RNA secondary structure.

The possibilities of using a genetic algorithm for the prediction of RNA secondary structure were investigated. The algorithm, using the procedure of stepwise selection of the most fit structures (similarly to natural evolution), allows different models of fitness or driving forces determining RNA structure to be easily introduced. This can be used for simulation of the RNA folding process and for the investigation of possible folding pathways. Such an algorithm needs several modifications before it can predict RNA secondary structures. After modification, a fair number of correct stems are predicted, even when using computationally quick, but very crude, fitness criteria such as stem length and stacking energy, including elements of tertiary structure (pseudoknots). The fact that genetic algorithm simulation includes both stem formations and stem disruption allows one to observe intermediate structures that may be used in combination with phylogenetic or experimental research.

Algorithms↗

PubMed2001

Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation.

Automatic identification of sub-structures in multi-aligned sequences is of great importance for effective and objective structural/functional domain annotation, phylogenetic treeing and other molecular analyses. We present a segmentation algorithm that optimally partitions a given multi-alignment into a set of potentially biologically significant blocks, or segments. This algorithm applies dynamic programming and progressive optimization to the statistical profile of a multi-alignment in order to optimally demarcate relatively homogenous sub-regions. Using this algorithm, a large multi-alignment of eukaryotic 16S rRNA was analyzed. Three types of sequence patterns were identified automatically and efficiently: shared conserved domain; shared variable motif; and rare signature sequence. Results were consistent with the patterns identified through independent phylogenetic and structural approaches. This algorithm facilitates the automation of sequence-based molecular structural and evolutionary analyses through statistical modeling and high performance computation.

Algorithms↗

PubMed2002

New robust 3-D phase unwrapping algorithms: application to magnetic field mapping and undistorting echoplanar images.

The phase, as well as the magnitude, of MRI images can carry useful information. It may be used to encode flow or temperature, or to map the magnetic field for the undistorting of EPIs and automated shimming. In all cases, we measure the extra spin given to nuclei. Unfortunately, we can only measure the final phase of the spins: the rotation is wrapped into the range [-pi, +pi], and to obtain a measure of the parameter of interest the missing multiples of 2pi must be replaced--a process known as phase unwrapping. While simple in principle, standard phase unwrapping algorithms fail catastrophically in the presence of even small amounts of noise. Here we present a new algorithm for robust three-dimensional phase unwrapping, in which unwrapping is guided, so that it initially works on less noisy regions. We test the algorithm on simulated phase data, and on maps of magnetic field, which were then used to successfully undistort EPI images. The unwrapping algorithm could be directly applied to other kinds of phase data.

Acoustic Stimulation↗

PubMed1996

A tissue composition-based algorithm for predicting tissue:air partition coefficients of organic chemicals.

The objectives of the present study were (i) to develop an algorithm for predicting the tissue:air partition coefficients (PCs) of volatile organic chemicals (VOCs) and (ii) to apply this algorithm to predict the rat tissue:air PCs of 45 VOCs. The approach consisted of estimating the tissue:air PCs by dividing the tissue solubility of chemicals by their saturable vapor concentrations. The tissue solubility of chemicals was calculated as the sum total of their solubility in neutral lipid, phospholipid, and water fractions of tissues. The rat liver:air, muscle:air, and adipose tissue:air PCs predicted using this algorithm compared well with literature data available for several ketones, alcohols, acetate esters, alkanes, haloalkanes, aromatic hydrocarbons, and diethyl ether. The average ratios between the predicted and experimental values of the tissue:air PC values were 0.94 (liver), 0.93 (muscle), and 1.10 (adipose tissue). The mechanistic algorithm developed in the present study should be useful for predicting tissue:air PCs of VOCs and for verifying the current default assumption of considering tissue:air PCs to be species-invariant.

Adipose Tissue↗

PubMed1996

Evolutionary algorithms in computer-aided molecular design.

In recent years, search and optimisation algorithms inspired by evolutionary processes have been applied with marked success to a wide variety of problems in diverse fields of study. In this review, we survey the growing application of these 'evolutionary algorithms' in one such area: computer-aided molecular design. In the course of the review, we seek to summarise the work to date and to indicate where evolutionary algorithms have met with success and where they have not fared so well. In addition to this, we also attempt to discern some future trends in both the basic research concerning these algorithms and their application to the elucidation, design and modelling of chemical and biochemical structures.

Algorithms↗

PubMed1987

A comparative study of attenuation correction algorithms in single photon emission computed tomography (SPECT).

A computer based simulation method was developed to assess the relative effectiveness and availability of various attenuation compensation algorithms in single photon emission computed tomography (SPECT). The effect of the nonuniformity of attenuation coefficient distribution in the body, the errors in determining a body contour and the statistical noise on reconstruction accuracy and the computation time in using the algorithms were studied. The algorithms were classified into three groups: precorrection, post correction and iterative correction methods. Furthermore, a hybrid method was devised by combining several methods. This study will be useful for understanding the characteristics, limitations and strengths of the algorithms and searching for a practical correction method for photon attenuation in SPECT.

Algorithms↗

PubMed1996

Validation of a knowledge-based boundary detection algorithm: a multicenter study.

A completely operator-independent boundary detection algorithm for multigated blood pool (MGBP) studies has been evaluated at four medical centers. The knowledge-based boundary detector (KBBD) algorithm is nondeterministic, utilizing a priori domain knowledge in the form of rule sets for the localization of cardiac chambers and image features, providing a case-by-case method for the identification and boundary definition of the left ventricle (LV). The nondeterministic algorithm employs multiple processing pathways, where KBBD rules have been designed for conventional (CONV) imaging geometries (nominal 45 degrees LAO, nonzoom) as well as for highly zoomed and/or caudally tilted (ZOOM) studies. The resultant ejection fractions (LVEF) from the KBBD program have been compared with the standard LVEF calculations in 253 total cases in four institutions, 157 utilizing CONV geometry and 96 utilizing ZOOM geometries. The criteria for success was a KBBD boundary adequately defined over the LV as judged by an experienced observer, and the correlation of KBBD LVEFs to the standard calculation of LVEFs for the institution. The overall success rate for all institutions combined was 99.2%, with an overall correlation coefficient of r=0.95 (P<0.001). The individual success rates and EF correlations (r), for CONV and ZOOM geometers were: 98%, r=0.93 (CONV) and 100%, r=0.95 (ZOOM). The KBBD algorithm can be adapted to varying clinical situations, employing automatic processing using artificial intelligence, with performance close to that of a human operator.

Algorithms↗

PubMed1991

An algorithm for converting a virtual-bond chain into a complete polypeptide backbone chain.

A systematic analysis is presented of the algorithm for converting a virtual-bond chain, defined by the coordinates of the alpha-carbons of a given protein, into a complete polypeptide backbone. An alternative algorithm, based upon the same set of geometric parameters used in the Purisima-Scheraga algorithm but with a different "linkage map" of the algorithmic procedures, is proposed. The global virtual-bond chain geometric constraints are more easily separable from the loal peptide geometric and energetic constraints derived from, for example, the Ramachandran criterion, within the framework of this approach.

Algorithms↗

PubMed1996

A non-negative fast multiplicative algorithm in 3D scatter-compensated SPET reconstruction.

Single-photon emission tomographic (SPET) reconstruction can be improved, especially for noisy images, by using the iterative expectation-maximization of the maximum-likelihood (EM-ML) algorithm. Its application to clinical routine is, however, hampered by the high number of iterations necessary to achieve acceptable results. Therefore various methods have been developed to accelerate the EM-ML algorithm. In this paper a new accelerated EM-ML-like multiplicative algorithm is proposed for SPET reconstruction. Contrary to some other accelerating methods, it preserves two of the most important properties of the EM-ML, namely pixel positivity inside the patient body and null activity outside. The convergence speed is improved by a factor which can reach 100 in high spatial frequency or low count regions. Good estimates in the low count region are obtained without any smoothing, even at typical routine clinical count rates. The algorithm used in conjunction with the 3D effective one scatter path model provides high-quality SPET images and accurate quantitation.

Adult↗

PubMed2000

Prototype algorithm for automated determination of gastric slow wave characteristics.

An algorithm for determining the frequency and propagation time of the gastric slow wave has been designed for integration into a demand gastric pacing system. The algorithm analyses the serosal activity in both the time and frequency domains, and the results are compared to produce a conclusion only when the values are within 5% of each other. Thus, the probability of inappropriate intervention is reduced, at the expense of unidentified segments. The system is verified by comparing the conclusions produced by the algorithm with conclusions from hand analysis of seven canine and one human serosal recordings. The algorithm correctly identifies the slow-wave frequency in the distal portion of the stomach for 90% of the segments, while producing no incorrect results. Slow-wave propagation times in the antrum are correctly identified for 84% of the segments, with no incorrect identifications.

Algorithms↗

PubMed2005

Algorithm for ventricular capture verification based on the mechanical evoked response.

Automatic pacemaker capture verification is important for maintaining safety and low energy consumption in pacemaker patients. A new algorithm was developed, based on impedance measurement between pacing electrode poles, which reflects the distribution of the conducting medium between the poles and changes with effective contraction. Data acquired during pacemaker implant in 17 subjects were analysed, with intracardiac impedance recorded while pacing was performed in the ventricle at varying energies, resulting in multiple-captured and non-captured beats. The impedance signals of all captured/non-captured beats were analysed using three different algorithms, based on the morphology of the impedance signal. The algorithm decision for each beat was compared with an actual capture or non-capture, as determined from the simultaneous recording of surface ECG. Two of the three algorithms (Z1 and Zn) were based on impedance values, and one (Z'n) was based on the first derivative of the impedance. Z1 was based on a single sample, whereas Z'n and Z'n were based on several samples in each beat. The total accuracy for each was Z1: 43%, Zn: 87%, Z'n: 92%. It was concluded that impedance-based capture verification is feasible, that a multiple rather than single sample approach for signal classification is both feasible and superior, and that first derivative analysis with multiple samples (Z'n) provides the best results.

Aged↗

PubMed2004

Probe selection algorithm for oligonucleotide array-based medium-resolution genotyping.

Medium-resolution genotyping has the goal of distinguishing different subgroups instead of each element in a group. An oligonucleotide array provides an inexpensive, high-throughput method to identify differences in DNA sequence among individuals, which is fundamental for genotyping. As the cost and difficulty of designing and fabricating the oligonucleotide array dramatically increase with the number of probes used, it is therefore important to have a design with a minimum number of probes meeting the requirement of medium-resolution genotyping. The first algorithm for designing and selecting probes for oligonucleotide array-based medium-resolution typing is reported. The goal in deriving the algorithm was to select a minimum number of probes from a large probe set on the premise of minimum loss of resolution. The algorithm, which was based on entropy, conditional entropy and mutual information theory, was used to select the minimum number of probes from a large probe set. The algorithm was tested on a human leukocyte antigen (HLA) sequence data set Thirty probes were selected from 390 probes for HLA-A, and 60 probes were selected from 767 probes for HLA-B. Although the number of probes was reduced by almost ten times, the distinguishability was reduced only a little, by 0.45% (from 99.90% to 99.45%) for HLA-A and 0.27% (from 99.84% to 99.57%) for HLA-B, respectively. This is a satisfactory and practical result.

Algorithms↗