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PubMed1997

Evaluation of an algorithm to identify women with carcinoma of the breast.

Although claims data are increasingly being used to measure and manage the cost and quality of health care, few studies have evaluated algorithms developed for such analyses. Therefore, the present study was performed to evaluate prospectively a previously published algorithm used to identify women with the new diagnosis of carcinoma of the breast. This algorithm had been developed from the patterns of claims that suggested common clinical presentations of carcinoma of the breast. In the present study, this algorithm was used to identify 177 potential cases of women with newly diagnosed carcinoma of the breast from the claims database of a large health maintenance organization (HMO). The algorithm's positive predictive value for cases identified in the present study was 83% (147/177). To attempt to improve upon the positive predictive value, multiple modifications of the algorithm were performed. The previously defined best modification of the initial algorithm yielded a positive predictive value of 84% (147/174) in the present study with the loss of none of the true positive cases. These results demonstrate that logic-based algorithms can be used as a valid and efficient method of identifying large numbers of new breast cancer cases from claims data. This algorithm provides a powerful tool to perform health care analysis and research for women with newly diagnosed carcinoma of the breast.

Aged↗
PubMed2002

The effect of a hepatitis serology testing algorithm on laboratory utilization.

RATIONALE, AIMS AND OBJECTIVES: Laboratory testing algorithms use patient and laboratory data to identify the optimal testing strategy for patients. Studies have shown that these algorithms can decrease test utilization. Since over-utilization of hepatitis serological tests was suspected, a hepatitis serology testing algorithm was initiated in Ontario, Canada. This study determined the effects of this algorithm on utilization. METHODS: Population-based retrospective observational study, involving all patients having viral hepatitis serological testing at private laboratories in Ontario, Canada, between July 1991 and December 1999. Prior to the testing algorithm, physicians listed the required specific antigens and antibodies on the test requisition form. In September 1996, the form was changed so that physicians identified the clinical indication--acute hepatitis, chronic hepatitis or immune status testing--for hepatitis serology testing. Therefore, the algorithm introduced a new 'tick-box' to the requisition form. Tests conducted by the laboratory depended upon which indication was chosen. Rates for hepatitis serological testing were calculated using population-based claims data. RESULTS: Time-series modelling showed that the testing algorithm was associated with a slight but significant increase in the use of hepatitis serology (P < 0.05). The algorithm was associated with an increase of 30 serological tests per 100,000 population per month. CONCLUSIONS: Introducing a testing algorithm for hepatic viral serology in Ontario did not significantly decrease hepatitis serology utilization and may be associated with a slight, but significant, increase in serology utilization rates.

Algorithms↗
PubMed2001

Computational and performance aspects of PCA-based face-recognition algorithms.

Algorithms based on principal component analysis (PCA) form the basis of numerous studies in the psychological and algorithmic face-recognition literature. PCA is a statistical technique and its incorporation into a face-recognition algorithm requires numerous design decisions. We explicitly state the design decisions by introducing a generic modular PCA-algorithm. This allows us to investigate these decisions, including those not documented in the literature. We experimented with different implementations of each module, and evaluated the different implementations using the September 1996 FERET evaluation protocol (the de facto standard for evaluating face-recognition algorithms). We experimented with (i) changing the illumination normalization procedure; (ii) studying effects on algorithm performance of compressing images with JPEG and wavelet compression algorithms; (iii) varying the number of eigenvectors in the representation; and (iv) changing the similarity measure in the classification process. We performed two experiments. In the first experiment, we obtained performance results on the standard September 1996 FERET large-gallery image sets. In the second experiment, we examined the variability in algorithm performance on different sets of facial images. The study was performed on 100 randomly generated image sets (galleries) of the same size. Our two most significant results are (i) changing the similarity measure produced the greatest change in performance, and (ii) that difference in performance of +/- 10% is needed to distinguish between algorithms.

Algorithms↗
PubMed1998

Evaluation of segmentation algorithms for generation of patient models in radiofrequency hyperthermia.

Time-efficient and easy-to-use segmentation algorithms (contour generation) are a precondition for various applications in radiation oncology, especially for planning purposes in hyperthermia. We have developed the three following algorithms for contour generation and implemented them in an editor of the HyperPlan hyperthermia planning system. Firstly, a manual contour input with numerous correction and editing options. Secondly, a volume growing algorithm with adjustable threshold range and minimal region size. Thirdly, a watershed transformation in two and three dimensions. In addition, the region input function of the Helax commercial radiation therapy planning system was available for comparison. All four approaches were applied under routine conditions to two-dimensional computed tomographic slices of the superior thoracic aperture, mid-chest, upper abdomen, mid-abdomen, pelvis and thigh; they were also applied to a 3D CT sequence of 72 slices using the three-dimensional extension of the algorithms. Time to generate the contours and their quality with respect to a reference model were determined. Manual input for a complete patient model required approximately 5 to 6 h for 72 CT slices (4.5 min/slice). If slight irregularities at object boundaries are accepted, this time can be reduced to 3.5 min/slice using the volume growing algorithm. However, generating a tetrahedron mesh from such a contour sequence for hyperthermia planning (the basis for finite-element algorithms) requires a significant amount of postediting. With the watershed algorithm extended to three dimensions, processing time can be further reduced to 3 min/slice while achieving satisfactory contour quality. Therefore, this method is currently regarded as offering some potential for efficient automated model generation in hyperthermia. In summary, the 3D volume growing algorithm and watershed transformation are both suitable for segmentation of even low-contrast objects. However, they are not always superior to user-friendly manual programs for contour generation. When the volume growing algorithm is used, the contours have to be postprocessed with suitable filters. The watershed transformation has a large potential if appropriately developed to 3D sequences and 3D interaction features. After all, the practicality and feasibility of every segmentation method critically depend on various details of the user software as pointed out in this article.

Algorithms↗
PubMed2004

Cone-beam and fan-beam image reconstruction algorithms based on spherical and circular harmonics.

A cone-beam image reconstruction algorithm using spherical harmonic expansions is proposed. The reconstruction algorithm is in the form of a summation of inner products of two discrete arrays of spherical harmonic expansion coefficients at each cone-beam point of acquisition. This form is different from the common filtered backprojection algorithm and the direct Fourier reconstruction algorithm. There is no re-sampling of the data, and spherical harmonic expansions are used instead of Fourier expansions. As a special case, a new fan-beam image reconstruction algorithm is also derived in terms of a circular harmonic expansion. Computer simulation results for both cone-beam and fan-beam algorithms are presented for circular planar orbit acquisitions. The algorithms give accurate reconstructions; however, the implementation of the cone-beam reconstruction algorithm is computationally intensive. A relatively efficient algorithm is proposed for reconstructing the central slice of the image when a circular scanning orbit is used.

Algorithms↗
PubMed2004

Static conductivity imaging using variational gradient Bz algorithm in magnetic resonance electrical impedance tomography.

A new image reconstruction algorithm is proposed to visualize static conductivity images of a subject in magnetic resonance electrical impedance tomography (MREIT). Injecting electrical current into the subject through surface electrodes, we can measure the induced internal magnetic flux density B = (Bx, By, Bz) using an MRI scanner. In this paper, we assume that only the z-component Bz is measurable due to a practical limitation of the measurement technique in MREIT. Under this circumstance, a constructive MREIT imaging technique called the harmonic Bz algorithm was recently developed to produce high-resolution conductivity images. The algorithm is based on the relation between inverted delta2Bz and the conductivity requiring the computation of inverted delta2Bz. Since twice differentiations of noisy Bz data tend to amplify the noise, the performance of the harmonic Bz algorithm is deteriorated when the signal-to-noise ratio in measured Bz data is not high enough. Therefore, it is highly desirable to develop a new algorithm reducing the number of differentiations. In this work, we propose the variational gradient Bz algorithm where Bz is differentiated only once. Numerical simulations with added random noise confirmed its ability to reconstruct static conductivity images in MREIT. We also found that it outperforms the harmonic Bz algorithm in terms of noise tolerance. From a careful analysis of the performance of the variational gradient Bz algorithm, we suggest several methods to further improve the image quality including a better choice of basis functions, regularization technique and multilevel approach. The proposed variational framework utilizing only Bz will lead to different versions of improved algorithms.

Algorithms↗
PubMed1992

Dynamic programming algorithms for restriction map comparison.

For most sequence comparison problems there is a corresponding map comparison algorithm. While map data may appear to be incompatible with dynamic programming, we show in this paper that the rigor and efficiency of dynamic programming algorithms carry over to the map comparison algorithms. We present algorithms for restriction map comparison that deal with two types of map errors: (i) closely spaced sites for different enzymes can be ordered incorrectly, and (ii) closely spaced sites for the same enzyme can be mapped as a single site. The new algorithms are a natural extension of a previous map comparison model. Dynamic programming algorithms for computing optimal global and local alignments under the new model are described. The new algorithms take about the same order of time as previous map comparison algorithms. Programs implementing some of the new algorithms are used to find similar regions within the Escherichia coli restriction map of Kohara et al.

Algorithms↗
PubMed2004

Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays.

MOTIVATION: Recent years' exponential increase in DNA microarrays experiments has motivated the development of many signal quantitation (SQ) algorithms. These algorithms perform various transformations on the actual measurements aimed to enable researchers to compare readings of different genes quantitatively within one experiment and across separate experiments. However, it is relatively unclear whether there is a 'best' algorithm to quantitate microarray data. The ability to compare and assess such algorithms is crucial for any downstream analysis. In this work, we suggest a methodology for comparing different signal quantitation algorithms for gene expression data. Our aim is to enable researchers to compare the effect of different SQ algorithms on the specific dataset they are dealing with. We combine two kinds of tests to assess the effect of an SQ algorithm in terms of signal to noise ratio. To assess noise, we exploit redundancy within the experimental dataset to test the variability of a given SQ algorithm output. For the effect of the SQ on the signal we evaluate the overabundance of differentially expressed genes using various statistical significance tests. RESULTS: We demonstrate our analysis approach with three SQ algorithms for oligonucleotide microarrays. We compare the results of using the dChip software and the RMAExpress software to the ones obtained by using the standard Affymetrix MAS5 on a dataset containing pairs of repeated hybridizations. Our analysis suggests that dChip is more robust and stable than the MAS5 tools for about 60% of the genes while RMAExpress is able to achieve an even greater improvement in terms of signal to noise, for more than 95% of the genes.

Algorithms↗
PubMed1996

Bioavailability algorithms in setting Recommended Dietary Allowances: lessons from iron, applications to zinc.

In addition to determining the amounts of isolated nutrients required for physiological function and homeostatic control, setting Recommended Dietary Allowances requires a consideration of nutrient bioavailability from foods in common diets. Bioavailability algorithms, or mathematical models to estimate nutrient bioavailability from different diets, have great appeal to help establish recommended intakes and identify beneficial dietary modifications. Accurate algorithms are difficult to develop because of the chemical complexity of the food supply and the numerous interactions that affect the bioavailability of mineral elements. A combination of reductionist and holistic approaches is necessary to identify the effects of isolated dietary components, and then to evaluate these effects in the complicated matrix of a whole diet. The most extensive development of bioavailability algorithms for mineral nutrients has been for iron, and understanding the strengths and weaknesses of the iron algorithms may help in development of algorithms for other inorganic nutrients such as zinc. Examples are provided to indicate the possible revision of iron bioavailability algorithms, the difficulty of verifying the iron bioavailability algorithms with iron status indices, and the possible development of zinc bioavailability algorithms. Bioavailability must be considered in the context of the biological control of mineral absorption, utilization and excretion, which may outweigh the importance of mineral bioavailability from diets in affluent countries with a varied and abundant food supply. While bioavailability algorithms may be helpful in estimating the effects of dietary changes or recommendations, and in improving diets of populations with a high incidence of deficiency of the mineral, they are not as yet sufficiently developed and validated for setting quantitative recommendations for "bioavailable" mineral intake.

Algorithms↗
PubMed2003

A statistical sampling algorithm for RNA secondary structure prediction.

An RNA molecule, particularly a long-chain mRNA, may exist as a population of structures. Further more, multiple structures have been demonstrated to play important functional roles. Thus, a representation of the ensemble of probable structures is of interest. We present a statistical algorithm to sample rigorously and exactly from the Boltzmann ensemble of secondary structures. The forward step of the algorithm computes the equilibrium partition functions of RNA secondary structures with recent thermodynamic parameters. Using conditional probabilities computed with the partition functions in a recursive sampling process, the backward step of the algorithm quickly generates a statistically representative sample of structures. With cubic run time for the forward step, quadratic run time in the worst case for the sampling step, and quadratic storage, the algorithm is efficient for broad applicability. We demonstrate that, by classifying sampled structures, the algorithm enables a statistical delineation and representation of the Boltzmann ensemble. Applications of the algorithm show that alternative biological structures are revealed through sampling. Statistical sampling provides a means to estimate the probability of any structural motif, with or without constraints. For example, the algorithm enables probability profiling of single-stranded regions in RNA secondary structure. Probability profiling for specific loop types is also illustrated. By overlaying probability profiles, a mutual accessibility plot can be displayed for predicting RNA:RNA interactions. Boltzmann probability-weighted density of states and free energy distributions of sampled structures can be readily computed. We show that a sample of moderate size from the ensemble of an enormous number of possible structures is sufficient to guarantee statistical reproducibility in the estimates of typical sampling statistics. Our applications suggest that the sampling algorithm may be well suited to prediction of mRNA structure and target accessibility. The algorithm is applicable to the rational design of small interfering RNAs (siRNAs), antisense oligonucleotides, and trans-cleaving ribozymes in gene knock-down studies.

Algorithms↗
PubMed2005

Limitations and potentials of current motif discovery algorithms.

Computational methods for de novo identification of gene regulation elements, such as transcription factor binding sites, have proved to be useful for deciphering genetic regulatory networks. However, despite the availability of a large number of algorithms, their strengths and weaknesses are not sufficiently understood. Here, we designed a comprehensive set of performance measures and benchmarked five modern sequence-based motif discovery algorithms using large datasets generated from Escherichia coli RegulonDB. Factors that affect the prediction accuracy, scalability and reliability are characterized. It is revealed that the nucleotide and the binding site level accuracy are very low, while the motif level accuracy is relatively high, which indicates that the algorithms can usually capture at least one correct motif in an input sequence. To exploit diverse predictions from multiple runs of one or more algorithms, a consensus ensemble algorithm has been developed, which achieved 6-45% improvement over the base algorithms by increasing both the sensitivity and specificity. Our study illustrates limitations and potentials of existing sequence-based motif discovery algorithms. Taking advantage of the revealed potentials, several promising directions for further improvements are discussed. Since the sequence-based algorithms are the baseline of most of the modern motif discovery algorithms, this paper suggests substantial improvements would be possible for them.

Algorithms↗
PubMed1990

A modified algorithm of the single pool urea kinetic model.

Urea Kt/V, calculated according to the variable volume single pool urea kinetic model (UKM), has been accepted as the yardstick reflecting the adequacy of haemodialysis therapy. However, the classical algorithm of UKM requires great care in dialyser urea clearance (K) measurement in order to avoid major inaccuracies in estimating the urea distribution volume (V). Thus, we suggest a modified algorithm of UKM which avoids the measurement of K. It assumes an arbitrary V value and then calculates kinetically K as a function of the assumed V value. The rationale of the modified algorithm can be derived from the knowledge that the classical algorithm imposes a proportionality ration between K and V: given a particular set of data, a change in the attributed value of K leads to a proportional change in the calculated V value, so that the ratio K/V remains nearly constant. Aims of the study were (1) to validate the modified algorithm by comparing the resulting Kt/V and normalised protein catabolic rate (NPCR) values with the homologous ones obtained using the classical algorithm in a group of 33 patients on thrice-weekly haemodialysis; plasma water urea concentrations were used with the classical algorithm (CApw) and the modified algorithm (MApw); and (2) to verify the possibility of using plasma urea concentrations with the modified algorithm (MAp) instead of the more rigorous plasma water concentrations. NPCR (g/kg per day) was 1.33 +/- 0.05 in CApw, 1.29 +/- 0.05 in MApw and 1.28 +/- 0.04 in MAp. Kt/V was 1.27 +/- 0.03 in CApw, 1.25 +/- 0.03 in MApw and 1.26 +/- 0.03 in MAp.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗
PubMed1995

The NRMP matching algorithm revisited: theory versus practice. National Resident Matching Program.

The authors examine the algorithm used by the National Resident Matching Program (NRMP) in its centralized matching of applicants to U.S. residency programs ("the Match"). Their goal is to evaluate the current NRMP matching algorithm to determine whether it still fulfills its intended purpose adequately and whether changes could be made that would improve the Match. They describe the basic NRMP algorithm and many of the variations of the matching process ("match variations") incorporated over the last 20 years to meet participants' requirements. An overview of the current state of the theory of preference matching is presented, including descriptions of the characteristics of stable matches in general, program-optimal and applicant-optimal matchings, and strategies for formulating preference lists. The characteristics of the current NRMP algorithm are then compared with the theoretical findings. Research conducted long after the original NRMP algorithm was devised has shown that an algorithm that produces stable matches is the best approach for matching applicants to positions. In the absence of requirements to satisfy match variations, the NRMP's deferred-acceptance algorithm produces a program-optimal stable match. When match variations, such as those handled by the NRMP, must be introduced, it is possible that no stable matching exists, and the resulting matching produced by the NRMP algorithm may not be program-optimal. The question of program-optimal versus applicant-optimal matchings is discussed. Theoretical and empirical evidence currently available suggest that differences between these two kinds of matchings are likely to be small. However, further tests and research are needed to assess the real differences in the results produced by different stable matching algorithms that produce program-optimal or applicant-optimal stable matches.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗
PubMed2005

Sedation algorithm in critically ill patients without acute brain injury.

OBJECTIVE: To determine whether use of a sedation algorithm to promote a high level of tolerance to the intensive care environment and preserve consciousness affected time to arousal and duration of mechanical ventilation in patients without acute brain injury. DESIGN: Two-phase, prospective, controlled study. SETTING: University-affiliated medical intensive care unit. PATIENTS: : Patients without acute brain injury requiring mechanical ventilation for at least 24 hrs. INTERVENTIONS: During the control phase, sedatives and analgesics were adjusted according to the physician's decision. During the algorithm phase, sedatives and analgesics were adjusted according to an algorithm developed by a multidisciplinary team including nurses and physicians. The algorithm was based on regular assessments of consciousness and tolerance to the intensive care unit environment using the Adaptation to Intensive Care Environment instrument and was designed to achieve tolerance and maintain a high level of consciousness. Standard practices, including weaning from the ventilator, were the same during both study phases. MEASUREMENTS AND MAIN RESULTS: A total of 102 patients were enrolled (control group, n = 54; algorithm group, n = 48). Median duration of mechanical ventilation was significantly shorter in the algorithm group (4.4 days [interquartile range, 2.1-9.8]) compared with the control group (10.3 days [3.5-17.2], p = .014), representing a 57.3% reduction. In Cox multivariate analysis, the risk of remaining on mechanical ventilation was 0.48 times (95% confidence interval, 0.29-0.78) lower for algorithm patients compared with controls. The median time to arousal was also significantly shorter in patients in the algorithm group (2 days [2-5]) compared with the control group (4 days [2-9], p = .006). CONCLUSIONS: The use of a sedation algorithm to promote tolerance to the intensive care environment and preserve consciousness in patients without acute brain injury resulted in a marked decrease in the duration of mechanical ventilation. This reduction was at least partly attributable to a shorter time to arousal after initiation of mechanical ventilation.

Adult↗
PubMed2004

A pharmacotherapy algorithm for stabilization and maintenance of pediatric bipolar disorder.

OBJECTIVE: To assess the feasibility and effectiveness of an evidence-based pharmacotherapy algorithm in the treatment of pediatric bipolar disorder. METHOD: The study reports the results of a study of 64 bipolar type I subjects who were treated according to an algorithm developed in our specialty clinic. All subjects had been diagnosed using the Washington University in St. Louis Schedule for Affective Disorders and Schizophrenia. Subjects scored an average of 28 (+/- 4) on the baseline Young Mania Rating Scale. All subjects were assessed over an 18-month period. In addition, we were able to match 17 of the 64 subjects in the algorithm sample for gender, age, ethnicity, socioeconomic status, and diagnosis with an equal number of subjects in a psychopharmacology clinic who received treatment as usual. RESULTS: Prescribing clinicians were able to implement primary and secondary strategies, including detailed tactics of medication choices in the algorithm group. Growth curve analysis of the total algorithm group showed strong and significant improvement in symptoms. Analyses of the matched groups also showed strong effects for the treatment algorithm over treatment as usual. Treatment adherence and family satisfaction were higher in the algorithm group. CONCLUSION: An evidence-based, problem-solving pharmacotherapy algorithm is feasible and may be associated with better outcomes in the treatment of pediatric bipolar disorder. Randomized trials will be necessary to gather additional support for the algorithm's effectiveness.

Algorithms↗
PubMed2003

A new algorithm for metal artifact reduction in computed tomography: in vitro and in vivo evaluation after total hip replacement.

RATIONALE AND OBJECTIVES: To evaluate a newly developed algorithm for metal artifact reduction (MAR) in Computed Tomography (CT). METHODS: A projection interpolation algorithm for MAR with threshold-based metal segmentation was developed. First, the algorithm was tested with a simulated hip phantom. On demand, the presence of metallic inserts was simulated, representing total hip endoprostheses. Second, CT data of 20 patient with total hip endoprosthesis were reconstructed with and without application of the MAR algorithm. Image quality was independently assessed by 2 experienced radiologists using a qualitative score. The results of the in vitro study were evaluated with the Student's t test. Results of the in vivo study were analyzed using a repeated-measure analysis of variance. RESULTS: Applying the MAR algorithm the phantom study showed no significant difference between images with and without simulated metal contributions. The patient study revealed improved image quality using the MAR algorithm. Results were statistically significant for fat (P=0.0097), vessels (P=0.0091), and bone (P=0.0005). Improvement of the image quality for muscle was not statistically significant (P=0.0287). CONCLUSIONS: A new algorithm for metal artifact reduction was successfully introduced into clinical routine. The algorithm led to a robust reduction of metal artifacts. The MAR algorithm may serve for an improvement in image quality in patients with metallic implants.

Aged↗
PubMed1999

A high-temporal resolution algorithm for quantifying organization during atrial fibrillation.

Atrial fibrillation (AF) has been described as a "random" or "chaotic" rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution. (approximately 300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.

Algorithms↗
PubMed1998

Accelerated iterative transmission CT reconstruction using an ordered subsets convex algorithm.

Iterative maximum likelihood (ML) transmission computed tomography algorithms have distinct advantages over Fourier-based reconstruction, but unfortunately require increased computation time. The convex algorithm [1] is a relatively fast iterative ML algorithm but it is nevertheless too slow for many applications. Therefore, an acceleration of this algorithm by using ordered subsets of projections is proposed [ordered subsets convex algorithm (OSC)]. OSC applies the convex algorithm sequentially to subsets of projections. OSC was compared with the convex algorithm using simulated and physical thorax phantom data. Reconstructions were performed for OSC using eight and 16 subsets (eight and four projections/subset, respectively). Global errors, image noise, contrast recovery, and likelihood increase were calculated. Results show that OSC is faster than the convex algorithm, the amount of acceleration being approximately proportional to the number of subsets in OSC, and it causes only a slight increase of noise and global errors in the reconstructions. Images and image profiles of the reconstructions were in good agreement. In conclusion, OSC and the convex algorithm result in similar image quality but OSC is more than an order of magnitude faster.

Algorithms↗