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At least 1,225 records · Page 68Linked to original sources
PubMed2006

Distance-based clustering of CGH data.

MOTIVATION: We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples. The goal is to develop a systematic way of placing patients with similar CGH imbalance profiles into the same cluster. Our expectation is that patients with the same cancer types will generally belong to the same cluster as their underlying CGH profiles will be similar. RESULTS: We focus on distance-based clustering strategies. We do this in two steps. (1) Distances of all pairs of CGH samples are computed. (2) CGH samples are clustered based on this distance. We develop three pairwise distance/similarity measures, namely raw, cosine and sim. Raw measure disregards correlation between contiguous genomic intervals. It compares the aberrations in each genomic interval separately. The remaining measures assume that consecutive genomic intervals may be correlated. Cosine maps pairs of CGH samples into vectors in a high-dimensional space and measures the angle between them. Sim measures the number of independent common aberrations. We test our distance/similarity measures on three well known clustering algorithms, bottom-up, top-down and k-means with and without centroid shrinking. Our results show that sim consistently performs better than the remaining measures. This indicates that the correlation of neighboring genomic intervals should be considered in the structural analysis of CGH datasets. The combination of sim with top-down clustering emerged as the best approach. AVAILABILITY: All software developed in this article and all the datasets are available from the authors upon request. CONTACT: juliu@cise.ufl.edu.

Algorithms↗
PubMed2006

Evaluation of uncertainty predictions and dose output for model-based dose calculations for megavoltage photon beams.

In many radiotherapy clinics an independent verification of the number of monitor units (MU) used to deliver the prescribed dose to the target volume is performed prior to the treatment start. Traditionally this has been done by using methods mainly based on empirical factors which, at least to some extent, try to separate the influence from input parameters such as field size, depth, distance, etc. The growing complexity of modern treatment techniques does however make this approach increasingly difficult, both in terms of practical application and in terms of the reliability of the results. In the present work the performance of a model-based approach, describing the influence from different input parameters through actual modeling of the physical effects, has been investigated in detail. The investigated model is based on two components related to megavoltage photon beams; one describing the exiting energy fluence per delivered MU, and a second component describing the dose deposition through a pencil kernel algorithm solely based on a measured beam quality index. Together with the output calculations, the basis of a method aiming to predict the inherent calculation uncertainties in individual treatment setups has been developed. This has all emerged from the intention of creating a clinical dose/MU verification tool that requires an absolute minimum of commissioned input data. This evaluation was focused on irregular field shapes and performed through comparison with output factors measured at 5, 10, and 20 cm depth in ten multileaf collimated fields on four different linear accelerators with varying multileaf collimator designs. The measurements were performed both in air and in water and the results of the two components of the model were evaluated separately and combined. When compared with the corresponding measurements the resulting deviations in the calculated output factors were in most cases smaller than 1% and in all cases smaller than 1.7%. The distribution describing the calculation errors in the total dose output has a mean value of -0.04% and a standard deviation of 0.47%. In the dose calculations a previously developed correction of the pencil kernel was applied that managed to contract the error distribution considerably. A detailed analysis of the predicted uncertainties versus the observed deviations suggests that the predictions indeed can be used as a basis for creating action levels and tracking dose calculation errors in homogeneous media.

Air↗
PubMedDate not supplied

Reliability and exactness of MRI-based volumetry: a phantom study.

This study investigated the influence of slice thickness, section orientation, contrast, shape, and sequence type on the exactness of MRI-based volumetry. Ni-doped agarose gel phantoms (4 to 46 ml) were scanned with a T1-weighted three-dimensional Fourier transform (FT) fast low-angle shot (FLASH) and a multiecho two-dimensional FT-Turbo spin-echo (SE) sequence. After segmentation with a three-dimensional region-growing algorithm, the geometric volume was measured considering the partial volume effect. The variability coefficient (Pearson) was .7%. The volumetric error increased with slice thickness, depending on the size and form of the object. Cross sections resulted in smaller error than longitudinal sections (finger-shaped phantoms, nonisotropic image data). Three-dimensional FT imaging. Results of slice thickness and section orientation experiments can be explained by the partial volume effect Higher errors in two-dimensional FT imaging were caused by object movements between two interleaved acquisitions. The study shows a considerable influence of the imaging parameters on the exactness, which depends on size and form of the structure of interest.

Algorithms↗
PubMed1989

Accuracy and reproducibility of clinically acquired two-dimensional echocardiographic mass measurements.

Left ventricular mass (LVM) measurements made by the truncated ellipsoid algorithm from clinical two-dimensional echocardiograms (2DE) were compared to autopsy weights in 37 patients. All six 2DE instruments were calibrated with an ultrasound phantom to standardize LVM measurements. Measurements were made by an experienced echocardiographer (LVME) and by an echocardiographer (LVMN) newly trained in LVM measurement from clinical 2DE tapes of patients with LV weights later confirmed at autopsy. LVME (r = 0.91, SEE +/- 41 gm) were more accurate than LVMN for all 2DE, but LVMN equalled LVME in accuracy for technically good 2DE. Interobserver variability was 36 gm, or 17% of LVM for all 2DE, and fell to 27 gm, or 12% of LVM for technically good 2DE. Segmental wall motion abnormalities and time from 2DE to death did not influence measurement accuracy significantly. LVM measurements by the 2DE truncated ellipsoid formula are accurate and reproducible in patients with normal and abnormal hearts.

Adult↗
PubMed2006

A Protein Classification Benchmark collection for machine learning.

Protein classification by machine learning algorithms is now widely used in structural and functional annotation of proteins. The Protein Classification Benchmark collection (http://hydra.icgeb.trieste.it/benchmark) was created in order to provide standard datasets on which the performance of machine learning methods can be compared. It is primarily meant for method developers and users interested in comparing methods under standardized conditions. The collection contains datasets of sequences and structures, and each set is subdivided into positive/negative, training/test sets in several ways. There is a total of 6405 classification tasks, 3297 on protein sequences, 3095 on protein structures and 10 on protein coding regions in DNA. Typical tasks include the classification of structural domains in the SCOP and CATH databases based on their sequences or structures, as well as various functional and taxonomic classification problems. In the case of hierarchical classification schemes, the classification tasks can be defined at various levels of the hierarchy (such as classes, folds, superfamilies, etc.). For each dataset there are distance matrices available that contain all vs. all comparison of the data, based on various sequence or structure comparison methods, as well as a set of classification performance measures computed with various classifier algorithms.

Algorithms↗
PubMed2006

Consistent sets of spectrophotometric chlorophyll equations for acetone, methanol and ethanol solvents.

A set of equations for determining chlorophyll a (Chl a) and accessory chlorophylls b, c2, c1 + c2 and the special case of Acaryochloris marina, which uses Chl d as its primary photosynthetic pigment and also has Chl a, have been developed for 90% acetone, methanol and ethanol solvents. These equations for different solvents give chlorophyll assays that are consistent with each other. No algorithms for Chl c compounds (c2, c1 + c2) in the presence of Chl a have previously been published for methanol or ethanol. The limits of detection (and inherent error, +/- 95% confidence limit), for chlorophylls in all organisms tested, was generally less than 0.1 microg/ml. The Chl a and b algorithms for green algae and land plants have very small inherent errors (< 0.01 microg/ml). Chl a and d algorithms for Acaryochloris marina are consistent with each other, giving estimates of Chl d/a ratios which are consistent with previously published estimates using HPLC and a rarely used algorithm originally published for diethyl ether in 1955. The statistical error structure of chlorophyll algorithms is discussed. The relative error of measurements of chlorophylls increases hyperbolically in diluted chlorophyll extracts because the inherent errors of the chlorophyll algorithms are constants independent of the magnitude of absorbance readings. For safety reasons, efficient extraction of chlorophylls and the convenience of being able to use polystyrene cuvettes, the algorithms for ethanol are recommended for routine assays of chlorophylls. The methanol algorithms would be convenient for assays associated with HPLC work.

Acetone↗
PubMed2004

Alternatives for potentially inappropriate medications in the elderly population: treatment algorithms for use in the Fleetwood Phase III Study.

OBJECTIVE: To provide estimates of the prevalence of potentially inappropriate medications used in eligible nursing facilities, to describe the development of evidence-based treatment algorithms for recommending safer alternative treatments to potentially inappropriate medications, and to provide the actual treatment algorithms developed for the Fleetwood Phase III study. DESIGN: Literature review, cross-sectional design. SETTING: Thirty North Carolina nursing facilities eligible for Fleetwood Phase III. PATIENTS, PARTICIPANTS: Algorithms developed for use by all pharmacists in the long-term care pharmacy serving the intervention facilities site for the Fleetwood Phase III study. INTERVENTIONS: Pharmacists are prospectively intervening directly with the prescriber to recommend a safer alternative to inappropriate medications using the standardized treatment algorithms developed for the study. MAIN OUTCOME MEASURE(S): Prevalence of potentially inappropriate medications used among residents and the development of 14 treatment algorithms suggesting appropriate alternatives to inappropriate medications. RESULTS: The percentage of potentially inappropriate medications used ranged from 0% to 13.2% at baseline in March 2002. We also found that evidence-based treatment algorithms were well received by consultant pharmacists at the intervention sites of the Fleetwood Phase III study. CONCLUSION: We have provided prevalence rates of potentially inappropriate medication use in nursing homes and developed treatment algorithms for pharmacists to use when making clinical recommendations regarding safer alternatives to potentially inappropriate medications in the elderly population. We are in the process of evaluating the effect of pharmacists' prospective interventions by using these standardized evidence-based treatment algorithms to reduce the prevalence of inappropriate medication use in intervention facilities.

Journal Article↗
PubMed2004

Bayesian analysis of risk factors for anovulation.

Two algorithms for assessing ovulatory status using daily urinary levels of oestrogen and progesterone metabolites have been applied to non-clinic-based, free-living populations of women. These relatively new methods for assessing ovarian function have been used to assess the potential adverse effects of occupational and environmental exposures, such as smoking, on the reproductive health of women. One algorithm has been validated against serum hormone measurements and gives good sensitivity and specificity for anovulation. However, a gold standard is generally not available in epidemiologic field studies in which these daily urine samples are collected. In this paper, we used Bayesian methods to estimate: (i) the probability of occurrence of anovulation, (ii) the sensitivity and specificity of the two algorithms, and (iii) the association between anovulation and smoking and other risk factors in the absence of a perfect test. We evaluated the two published algorithms for assessing ovulatory status, based on their cross-classified results applied to one randomly selected cycle from each woman in a sample of 338 employed women. We first assumed that the algorithms were independent, conditional on ovulatory status. Then, we used a dependence model to allow for correlation between the results of the two algorithms. We implemented a Bayesian logistic regression analysis that allowed the outcome measurement to be partially imperfect. We incorporated the posterior distributions for algorithm accuracy obtained from the dependence model as prior distributions for this logistic regression model. Then, we compared the results with those obtained from a standard multiple logistic approach using the algorithm determination of ovulatory status as if it were perfect. Our results indicated that increasing physical activity was associated with a significantly increased risk of anovulation; and smokers had a potentially, but not statistically significant, increased occurrence of anovulation.

Adult↗
PubMed2001

Automated prediction of 15N, 13Calpha, 13Cbeta and 13C' chemical shifts in proteins using a density functional database.

A database of peptide chemical shifts, computed at the density functional level, has been used to develop an algorithm for prediction of 15N and 13C shifts in proteins from their structure; the method is incorporated into a program called SHIFTS (version 4.0). The database was built from the calculated chemical shift patterns of 1335 peptides whose backbone torsion angles are limited to areas of the Ramachandran map around helical and sheet configurations. For each tripeptide in these regions of regular secondary structure (which constitute about 40% of residues in globular proteins) SHIFTS also consults the database for information about sidechain torsion angle effects for the residue of interest and for the preceding residue, and estimates hydrogen bonding effects through an empirical formula that is also based on density functional calculations on peptides. The program optionally searches for alternate side-chain torsion angles that could significantly improve agreement between calculated and observed shifts. The application of the program on 20 proteins shows good consistency with experimental data, with correlation coefficients of 0.92, 0.98, 0.99 and 0.90 and r.m.s. deviations of 1.94, 0.97, 1.05, and 1.08 ppm for 15N, 13Calpha, 13Cbeta and 13C', respectively. Reference shifts fit to protein data are in good agreement with 'random-coil' values derived from experimental measurements on peptides. This prediction algorithm should be helpful in NMR assignment, crystal and solution structure comparison, and structure refinement.

Algorithms↗
PubMed2005

Blood pressure response to transition from supine to standing posture using an orthostatic response algorithm.

Upon standing from a supine position, the normal response is an increase in heart rate to maintain blood pressure (BP). In patients with chronotropic incompetence, heart rate may not increase upon standing, and they may experience orthostatic hypotension (OH). We evaluated a new orthostatic response (OSR) pacing algorithm that uses an accelerometer signal to detect sudden activity following prolonged rest to trigger a 2 minutes increase in pacing rate to 94 bpm. Ten recipients of DDDR pacemakers which contain the OSR compensation algorithm (mean age = 77 +/- 9 years, 8 women) with sick sinus syndrome (n = 6) or atrioventricular block (n = 4) were studied. In all patients BP was measured before and 0.5, 1, 1.5, 2, and 3 minutes after standing at their programmed base rate. A 20 mmHg fall in systolic BP upon standing was observed in five patients (OH patients), while the other five were considered non-OH patients. The measurements were repeated with the OSR algorithm turned on. Mean BP was defined as 1/3 systolic BP + 2/3 diastolic BP. Baseline heart rate was significantly slower in OH patients (62 +/- 2 bpm) than non-OH patients (71 +/- 7 bpm, P < 0.05). In OH patients mean BP increased significantly upon standing (P < 0.05 for all comparisons) with the algorithm ON instead of decreasing with the algorithm OFF, at 1 minute (+3.4 vs -10.3 mmHg), 1.5 minutes (+7.0 vs -4.9 mmHg), 2 minutes (+1.6 vs -6.7 mmHg), and 3 minutes (+2.5 vs -8.5 mmHg). These preliminary results suggest that the OSR algorithm maintains BP upon standing in patients with OH.

Aged↗
PubMed2006

A general framework for biclustering gene expression data.

A large number of biclustering methods have been proposed to detect patterns in gene expression data. All these methods try to find some type of biclusters but no one can discover all the types of patterns in the data. Furthermore, researchers have to design new algorithms in order to find new types of biclusters/patterns that interest biologists. In this paper, we propose a novel approach for biclustering that, in general, can be used to discover all computable patterns in gene expression data. The method is based on the theory of Kolmogorov complexity. More precisely, we use Kolmogorov complexity to measure the randomness of submatrices as the merit of biclusters because randomness naturally consists in a lack of regularity, which is a common property of all types of patterns. On the basis of algorithmic probability measure, we develop a Markov Chain Monte Carlo algorithm to search for biclusters. Our method can also be easily extended to solve the problems of conventional clustering and checkerboard type biclustering. The preliminary experiments on simulated as well as real data show that our approach is very versatile and promising.

Algorithms↗
PubMed2006

Computer simulation of visual outcomes of wavefront-only corneal ablation.

PURPOSE: To evaluate the effectiveness, predicted visual outcome, and limitations of a corneal ablation algorithm that uses wavefront aberration measurement alone without the need for corneal shape information. SETTING: Contact Lens and Visual Optical Laboratory, School of Optometry, Queensland University of Technology, Brisbane, Australia. METHODS: Corneal topography and wavefront error data from 22 eyes of 11 potential refractive surgery candidates were used. A computer simulation of the corneal ablation was performed, and the predicted postoperative visual outcome was assessed by calculating the resulting wavefront root-mean-square (RMS) values and visual Strehl ratios. Additionally, the effect of ablation alignment error was examined. Finally, the visual outcomes of the wavefront-only corneal ablations were compared to those in an age-matched group of 20 emmetropic patients. RESULTS: Significant improvement in total and higher-order wavefront RMS was achieved postoperatively in both an ideal setting and in the case of ablation alignment errors. The predicted improvement in visual Strehl ratio in the potential refractive surgery candidates was significantly better than that in the untreated emmetropes. After additional simulated decentration of the pupil center by 150 microm, the result was slightly worse, but the change was found to not be significant when compared to the retinal image quality of emmetropes. CONCLUSIONS: Wavefront-only corneal ablation algorithms could potentially lead to significantly better visual outcomes than those normally encountered in untreated emmetropes, provided that the alignment error is not large. The presented methodology may be used as a screening tool to predict patients' visual outcomes before the surgery.

Adolescent↗
PubMed2005

A new method for accurate and fast measurement of 3D eye movements.

Videooculography (VOG) is an eye movement measurement method used in the objective evaluation of vestibulo-ocular reflexes (VOR). An important requirement of VOG is to accurately estimate pupil center and ocular torsion, irrespective of drooping eyelids, eyelashes, corneal reflection, and blinking. Finding the accurate center of the pupil is particularly important in three-dimensional VOG, since otherwise, significant errors can occur in measuring torsional eye movement. A fast algorithm was proposed to accurately ascertain the pupil center, in spite of the complicating factors mentioned above. In this study, real-time three-dimensional VOG, which can measure horizontal, vertical, and torsional eye movements and calculate the pupil radius, was implemented using the proposed method. When the pupil radius was determined, the vertical position was measured within an error margin of less than 3%, even though only 10% of the pupil was visible. The time required to measure both three-dimensional eye movements and the pupil radius was less than 16 ms. Thus, eye movements can be measured in real-time. The resolutions of horizontal, vertical, and torsional eye movement were 0.2 degrees, 0.2 degrees, and 0.1 degrees, respectively, with maximum ranges of +/- 35 degrees, +/- 25 degrees, and +/- 18 degrees.

Algorithms↗
PubMed2002

The application of PET-MR image registration in the brain.

The coregistration in three-dimensional space of positron emission tomography (PET) and magnetic resonance (MR) image volumes has, over the last decade, become a matter of routine in the analysis of brain PET studies. The ability to objectively localize small regions of interest in PET using images more closely correlated to tissue structure has itself improved the effective resolution of PET. There are a number of highly effective software packages for image coregistration available in the public domain. Voxel-by-voxel coregistration, involving little or no intervention from the user can, on today's computing hardware, provide fast and accurate registration with little or no pre-processing and algorithms based on mutual information measures now seem to be the mathematical method of choice. Registration may be applied in a number of ways. Rigid body registration is used to match a single subject's brain scanned using either different imaging modalities or as serial scans with the same modality. Increasingly, this technique is being extended to studies of disease involving regional atrophy, where location and extent of tissue loss can be identified. Non-linear registration can be used to warp a subject's brain onto a template, atlas or other standardized guide. While numerous examples are available of the added value produced by image registration in the brain, similar examples are not yet available from registration in the torso, where the problem is much more complex. It is here that newly emerging hardware such as combined PET/CT scanners may prove their worth.

Algorithms↗
PubMed1993

Band features as classification measures for G-banded chromosome analysis.

Modern automatic and semiautomatic karyotyping systems employ algorithms that use chromosome length and centromeric index as well as other intact chromosome measures. These measures offer correct classification rates near 95%. An algorithm is presented that utilizes local dark band features and position (position from one end of the chromosome, band-width, band-height above light band background, integrated optical density above light band background, and a shape feature) and is based on maximum likelihood of the multivariate normal distribution for the feature vector. The algorithm was tested on two data sets: 179 metaphases from C. Lundsteen at the Rigshospitalet, Copenhagen, and 50 metaphases from The University of Texas M. D. Anderson Cancer Center. The Copenhagen set achieved an overall correct classification rate of 94.6% when classifying itself, a rate comparable to other algorithms. This classifier relies on local band features rather than global chromosome characteristics and is therefore directly extensible to metaphase and prophase chromosome subsegments and to structural abnormalities.

Algorithms↗
PubMed2004

Assessment of two-dimensional induced accelerations from measured kinematic and kinetic data.

A simple algorithm is presented to calculate the induced accelerations of body segments in human walking for the sagittal plane. The method essentially consists of setting up 2x4 force equations, 4 moment equations, 2x3 joint constraint equations and two constraints related to the foot-ground interaction. Data needed for the equations are, next to masses and moments of inertia, the positions of ankle, knee and hip. This set of equations is put in the form of an 18x18 matrix or 20x20 matrix, the solution of which can be found by inversion. By applying input vectors related to gravity, to centripetal accelerations or to muscle moments, the 'induced' accelerations and reaction forces related to these inputs can be found separately. The method was tested for walking in one subject. Good agreement was found with published results obtained by much more complicated three-dimensional forward dynamic models.

Acceleration↗
PubMed2004

Coronary flow reserve measurements in hypertension.

Taken together, the diagnostic algorithm is leaded by a simple ECG stress test. In case of ST-segment depression the preferred image test should be stress ECG to bring patients at high risk for significant epicardial coronary artery stenosis to coronary angiography (and revascularization). In case of the lack of wall motion abnormalities (during stress-echo test) or absence of epicardial stenosis one may further assess coronary flow reserve with noninvasive Doppler harmonic echocardiography. For ultimate quantitative assessment invasive procedures, such as argon dilution or intracoronary Doppler techniques, represent the appropriate approach. Treatment of microvascular disease may be followed-up by these new noninvasive diagnostic approaches in future and also, at present, by monitoring ST-segment depression.

Angiography↗