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PubMed1994

Preliminary experience using an optimized three-point transformation algorithm for spatial registration of coordinate systems: a method of noninvasive localization using frame-based stereotactic guidance systems.

This study describes the use of an optimized three-point transformation algorithm to spatially cross-register a volumetric computerized tomographic scan or magnetic resonance image data set with the coordinate system of a stereotactic frame. This algorithm was tested for accuracy using a scanned phantom in which calculated targets, using the Brown-Roberts-Wells (BRW) frame picket-fence algorithm as a standard, could be compared to physical targets measured using a BRW arc and phantom. These target values were then compared to target values calculated with the optimized three-point algorithm. This method was used for target localization in 21 patients. Following this noninvasive localization method, the standard BRW stereotactic system was used for guidance. The application accuracy of this frameless localization technique was within the limits of the scan slice thickness in 16 of 21 cases, with an average error of 2.11 mm in an average scan slice thickness of 3.1 mm. Intracranial targets were successfully reached in all cases without morbidity or mortality. The algorithm can be customized to cross-register image data sets with the coordinate systems of a wide variety of stereotactic guidance systems. The method increases the convenience and flexibility of frame-based stereotactic guidance by providing a means of noninvasive localization that can be accomplished electively at a separate time from the guidance part of a stereotactic operative procedure.

Aged↗

PubMed2004

Computer algorithms to detect bloodstream infections.

We compared manual and computer-assisted bloodstream infection surveillance for adult inpatients at two hospitals. We identified hospital-acquired, primary, central-venous catheter (CVC)-associated bloodstream infections by using five methods: retrospective, manual record review by investigators; prospective, manual review by infection control professionals; positive blood culture plus manual CVC determination; computer algorithms; and computer algorithms and manual CVC determination. We calculated sensitivity, specificity, predictive values, plus the kappa statistic (kappa) between investigator review and other methods, and we correlated infection rates for seven units. The kappa value was 0.37 for infection control review, 0.48 for positive blood culture plus manual CVC determination, 0.49 for computer algorithm, and 0.73 for computer algorithm plus manual CVC determination. Unit-specific infection rates, per 1,000 patient days, were 1.0-12.5 by investigator review and 1.4-10.2 by computer algorithm (correlation r = 0.91, p = 0.004). Automated bloodstream infection surveillance with electronic data is an accurate alternative to surveillance with manually collected data.

Algorithms↗

PubMed2000

Image-processing algorithms for behavior analysis of group-housed pigs.

Computational algorithms of image processing were developed and evaluated to select, by motion detection, images of resting artificial pigs and to segment the pigs (mixture of black and white pigs) from their background. Motion detection of the pigs was implemented by detecting interframe differences of postural behavioral images. This algorithm combines the advantages of likelihood ratio method and shading model method and shows a stable performance under noisy and dynamic illumination conditions. Segmentation of the pigs from their background was implemented by employing multilevel thresholding and background reference techniques. The algorithm automatically determines the number of thresholds needed and produces satisfactory segmentation when both black and white pigs with different image intensities are present at the same time (the most complicated situation). The reference background image is updated so that temporal changes in illumination and/or spatial changes of the pen condition have little effect on the performance of image segmentation. The algorithm employs statistical models of the pigs and background and Bayes hypothesis testing to obtain and update the exposed portion of the reference background. Linear filters were used in this process for updating the parameters. These algorithms will serve as essential components for a novel, behavior-based, interactive approach to assess and control thermal comfort of group-housed pigs, which is expected to result in enhanced animal health and well-being.

Algorithms↗

PubMedDate not supplied

Algorithm to correct hyperopic astigmatism with the Nidek EC-5000 excimer laser.

BACKGROUND: The efficacy of a new ablation algorithm for the correction of hyperopic astigmatism with the Nidek EC-5000 excimer laser was evaluated. METHODS: Twenty-five eyes with mean preoperative hyperopia of +3.76 +/- 1.70 D and a mean hyperopic cylinder of 2.20 +/- 0.80 D underwent photorefractive keratectomy (PRK) using a new algorithm with the Nidek EC-5000 excimer laser (software version 3.0). The new algorithm differed from previous algorithms in that less tissue was removed for the same amount of diopters, and there was less of a dioptric gradient between the optical zone and the transition zone. Mean preoperative spectacle-corrected visual acuity was 0.8 +/- 0.09. Minimum follow-up was 6 months. RESULTS: Mean postoperative spectacle corrected visual acuity (geometric mean) increased significantly to 0.89 +/- 0.1. The mean sphere decreased by 3.08 D and the mean cylinder by 1.60 D. CONCLUSION: Hyperopic PRK using the Nidek EC-5000 excimer laser with this new algorithm for hyperopic astigmatism appears to be safe and effective.

Adult↗

PubMedDate not supplied

No patient left behind: evaluation and design of intravenous insulin infusion algorithms.

OBJECTIVE: To define the characteristics of performance evaluation, algorithm design, and regulation of insulin delivery by which professionals and the healthcare system might differentiate between methodologies for intravenous insulin infusion. METHODS: Published performance criteria used in the assessment of intravenous insulin infusion algorithms are classified. The structure of intravenous insulin infusion formulae is reviewed, as are technologies that might lead to future improvement. RESULTS: Among published reports, no standardization was discernable for description of algorithm characteristics or performance. Except for time-to-target and hypoglycemic episodes, measures using the patient as unit of observation are not employed consistently. CONCLUSION: The healthcare system needs criteria for evaluation and minimal acceptable standards for assessing performance of any algorithm, decision support system, or closed-loop system for intravenous insulin infusion. Inclusion of patient-based measures is necessary to assess the ability of an algorithm to control variability between patients and within a given run. Standardization of performance reporting will help users to select appropriate methodologies.

Algorithms↗

PubMedDate not supplied

What makes a good staging algorithm: examples from regular exercise.

PURPOSE: This study retrospectively compared subjects from three unrelated studies using eight algorithms to stage exercise behavior. SUBJECTS AND SETTINGS: Study One included 936 employees involved in a smoking cessation study at four worksites--a medical center, retail store, manufacturing firm, and a government agency. Study Two included 19,212 members of a New England HMO; and Study Three included a convenience sample of 327 adult New Englanders. MEASURES: The eight algorithms used different descriptions of stages based on the transtheoretical model, as well as different definitions of exercise and response formats. RESULTS: Algorithms using longer, more precise definitions of exercise resulted in larger numbers of subjects being staged in precontemplation and contemplation in comparison to algorithms using shorter definitions, which tended to stage subjects in preparation and action. Maintenance was the most and preparation the least consistently described stage across algorithms. CONCLUSIONS: Alteration of the descriptions of stage and the definition of exercise has consequences for the staging of subjects. Definitions need to be explicit, stating all parameters needed to meet criterion, and subjects must be able to assess themselves. Either a 5-Choice or a true/false response format is effective in assessing stage.

Adult↗

PubMed2006

A stepwise drug treatment algorithm to obtain complete remission in depression: a Geneva study.

QUESTIONS UNDER STUDY/PRINCIPLES: We describe the proportion of severely depressed outpatients reaching complete remission at the different stages of a drug treatment algorithm. We compare several treatment options for SSRI (selective serotonin reuptake inhibitor) non-responders and test the feasibility of the algorithm in clinical conditions. METHODS: Patients with severe depressive disorders (ICD-10; MADRS > or = 25) admitted to an academic outpatient clinic were enrolled in this algorithm-guided sequential treatment protocol (starting with an SSRI and ending with a tricyclic, lithium, triodothyronine combination). The general principle of the algorithm was to boost the drug therapy in the event of non-response. RESULTS: 135 patients entered the study and 131 were eligible for analysis. From this group, 86 patients dropped out (65.6%), 40 reached complete remission (30.5%) and 5 patients did not reach remission at all (3.8%). In the 117 patients to whom a last observation carried forward approach was applied, the median improvement of the MADRS score was 48.0% (range -20.7%-100%), with 48.7% of patients considered responders, 23.1% partial responders and 28.2% non-responders. Median retention time was 8 weeks (range 2-34). CONCLUSIONS: This algorithm-guided antidepressant treatment was acceptable for clinicians and resulted in an elevated final response rate among study completers. However, the dropout rate was high, mainly due to treatment interruption or non-observance.

Adult↗

PubMed1999

A new Hybrid Monte Carlo algorithm for protein potential function test and structure refinement.

A new Hybrid Monte Carlo (HMC) algorithm has been developed to test protein potential functions and, ultimately, refine protein structures. The main principle of this algorithm is, in each cycle, a new trial conformation is generated by carrying out a short period of molecular dynamics (MD) iterations with a set of random parameters (including the MD time step, the number of MD steps, the MD temperature, and the seed for initial MD velocity assignment); then to accept or reject the new conformation on the basis of the Metropolis criterion. The novelty in this paper is that the potential in MD iterations is different from that in the MC step. In the former, it is a molecular mechanics potential, in the latter it is a knowledge-based potential (KBP). Directed by the KBP, the MD iteration is used to search conformational space for realistic conformations with low KBP energy. It circumvents the difficulty in using KBP functions directly in MD simulation, as KBP functions are typically incomplete, and do not always have continuous derivatives required for the calculation of the forces. The new algorithm has been tested in explorations of conformational space. In these test calculations the KBP energy was found to drop below the value for the native conformation, and the correlation between the root mean square deviation (RMSD) and the KBP energy was shown to be different from the test results in other references. At the present time, the algorithm is useful for testing new KBP functions. Furthermore, if a KBP function can be found for which the native conformation has the lowest energy and the energy/RMSD correlation is good, then this new algorithm also will be a tool for refinement of the theory-based structural models.

Algorithms↗

PubMed2000

Performance of ordered-subset reconstruction algorithms under conditions of extreme attenuation and truncation in myocardial SPECT.

UNLABELLED: We studied the bias and variance characteristics of the ordered-subset expectation maximization (OSEM) and rescaled block-iterative EM (RBIEM) iterative reconstruction algorithms in myocardial SPECT under extreme, but realistic, conditions. METHOD: We used the 2-dimensional mathematic cardiac torso phantom to simulate 2 patient anatomies: a large male with a raised diaphragm and a female with large breast size, approximating extreme cases of attenuation conditions found in the clinic. For each anatomy, realistic 201Tl projection data were simulated for a 180 degrees acquisition arc. Three cases of truncation for a 90 degrees-configured dual detector system were simulated: no truncation, moderate truncation, and extreme truncation. For each case, an ensemble of 250 noise simulations was generated, and each noisy dataset was reconstructed with the OSEM and RBIEM algorithms. The reconstructions modeled only the effects of nonuniform attenuation and used a range of subset configurations. Over the ensemble, we computed means and variances of activity in 8 regions of interest (ROIs) in the heart as a function of iteration. RESULTS: Under conditions of no truncation and moderate truncation, the results from OSEM and RBIEM were very close to those from maximum-likelihood EM (MLEM); in all cases, the difference in ROI means was <2.5%. For extreme truncation, the errors increased to as much as 11% with OSEM, but these were no greater than the errors for MLEM under the same conditions. The OSEM algorithm with 2 views per subset was found to result in much higher variance of ROI estimates for the same bias as compared with RBIEM or OSEM with 4 or more views per subset. CONCLUSION: The OSEM and RBIEM algorithms are at least as robust to highly attenuating patients and truncation as MLEM algorithm and can be adequate substitutes for MLEM, even in extreme cases. Clinical users should apply the smallest number of subsets that can be accommodated by allowable processing time to reduce image noise and variance in quantitative estimates.

Algorithms↗

PubMed2001

Early diagnosis of ectopic pregnancy. Does use of a strict algorithm decrease the incidence of tubal rupture?

OBJECTIVE: To determine if tubal rupture rates are decreased when a strict diagnostic algorithm is employed in the evaluation of women with suspected ectopic pregnancy as compared to individualized diagnostic methods. STUDY DESIGN: Between 1994 and 1996, a group of investigators at Charleston Area Medical Center employed a strict diagnostic algorithm consisting of serum quantitative human chorionic gonadotropin (hCG) levels, progesterone levels, ultrasound and endometrial curettage in order to expedite diagnosis when ectopic pregnancy was suspected (group A patients). Other practitioners employed traditional criteria in similar clinical situations (group B patients). Medical records of patients diagnosed with ectopic pregnancy in this period were retrospectively reviewed. Demographic data, clinical and laboratory characteristics, and rate of tubal rupture were compared. RESULTS: Sixty-one of 122 patients were diagnosed with ectopic pregnancy by strict criteria. These patients did not differ significantly from those evaluated by an individualized approach in regard to age, gravidity, parity or risk factors for ectopic pregnancy. Menstrual age, hCG levels and progesterone levels were similar as well. Group A patients had a median diagnostic interval of 2 days, with a range of 0-16. Group B patients had a median diagnostic interval of 8 days, with a range of 0-44 (P < .001). Of patients evaluated by this strict algorithm, 3.3% experienced rupture as compared to 23% of patients in group B (P < .001). CONCLUSION: Use of a strict diagnostic algorithm in the evaluation of patients with suspected ectopic pregnancy resulted in decreased tubal rupture rates. Such an algorithm could be disseminated to all locations for triage of patients and use in a standardized manner. This practice could result in a reduction in loss of reproductive function and mortality secondary to ectopic pregnancy.

Algorithms↗

PubMed1996

First use of cognitive algorithms in investigations under compensated gravity.

In the present paper the use of cognitive algorithms for solving a wide spectrum of problems which often arise in investigations under compensated gravity is suggested. Applying such algorithms in the preparation and performance of experiments provides a substantial assistance to the experimentator as the behaviour of complex processes can be described and predicted correctly even when unexpected perturbations occur. Furthermore, an essential advantage of cognitive computing consists in the fact that the description and optimisation of the processes considered are possible also in such cases in which the corresponding basic equations are not known or not treatable practically. For convenience, the basic ideas of cognitive algorithms are discussed here. Due to their special relevance for investigations under compensated gravity algorithms based on fuzzy logic (FL) and artificial neuronal networks (ANN) are elucidated more in detail. In order to illustrate some advantages of cognitive computing exemplary results for the flow field induced by coaxial rotating disks are given. This represents the first attempt to use the benefits provided by cognitive algorithms in investigations under compensated gravity. The flow field between rotating disks plays an important role not only in experiments under compensated gravity but also in a wide range of terrestrial applications. A comparison of the results found by solving the Navier-Stokes equations and those from the prediction performed by ANN adequately trained shows an excellent agreement. However, the calculation times needed by the ANN are significantly smaller than that of the direct numerical simulation. Therefore, the real time prediction of the results from a running experiment seems to be possible.

Algorithms↗

PubMed2001

Algorithm-based decision rules to safely reduce laboratory test ordering.

PURPOSE: Our study develops decision rules to define appropriate intervals at which repeat tests might be indicated for commonly ordered laboratory tests for hospitalized patients. METHODS: The final data set includes 5,632 adult patients admitted to the University of Virginia Hospital between July 1995 and December 1999. These patients had a hospital length of stay of five days or more and had results recorded for three routinely ordered laboratory tests for each of the first five days of their hospitalization. We use the serum potassium test to illustrate our algorithm-based decision rule methodology. RESULTS: Our decision rule begins with testing on the first two days of hospitalization and allows for repeat testing after observation of any non-normal values. The results show that the algorithm-based decision rule would lead to a 34% reduction for serum potassium tests for the first five days of hospitalization. Only one out of the 5,632 patients in our sample had a critical value that occurred only on a non-test day and, thus, was missed by the algorithm. CONCLUSIONS: The algorithm results are encouraging. We demonstrate that the number of tests can be reduced while missing critical values in only a small fraction of patients. Testing algorithms such as these can be used to reduce laboratory test ordering without compromising the quality of patient care.

Adult↗

PubMed2002

An optimization algorithm that incorporates IMRT delivery constraints.

An intensity-modulated beam optimization algorithm is presented which incorporates the delivery constraints into the optimization cycle. The optimization algorithm is based on the quasi-Newton method of iteratively solving minimization problems. The developed algorithm iteratively corrects the incident, pencil-beam-like, fluence to incorporate the delivery constraints. In the present study, the goal of the optimization algorithm is to achieve the best deliverable radiotherapy plan, subject to the constraints of the delivery technique described by a leaf-sequencing algorithm being applied concurrently. In general, if they are applied after, rather than during, the optimization cycle, the delivery constraints associated with the IMRT technique can produce local variations up to 6% in the 'optimized' dose (i.e., distribution without applied constraints) and reduce the degree of conformity, of the dose, to the PTV region. The optimization method has been applied to three IMRT delivery techniques: dynamic multileaf (DMLC), multiple-static-field (MSF) and slice-by-slice tomotherapy (NOMOS MIMiC). The beam profiles were generated for a prostate tumour with organs at risk being the rectum, bladder and femoral heads. The optimization method described was shown to generate optimum and deliverable IMRT plans for these three delivery techniques. In the case of the DMLC and MSF the optimization converged within 3-5 iterations to a mean PTV dose of 69.60 +/- 1.34 Gy and 69.71 +/- 1.34 Gy, respectively, while for NOMOS MIMiC approximately 10 iterations were needed to obtain 69.68 +/- 1.55 Gy. In addition to this, the IMRT optimization also yielded optimum fluence profiles when clustering was performed concurrently with the leaf-sequencer. An optimum between 8 and 15 clusters of equal fluence 'intensity' was shown to establish the best compromise between the number of fluence levels and the PTV dose coverage.

Algorithms↗

PubMed2002

A genotypic drug resistance interpretation algorithm that significantly predicts therapy response in HIV-1-infected patients.

OBJECTIVES: The development of a genotypic drug resistance interpretation algorithm, and the evaluation of its power to predict therapy outcome. DESIGN: A rule-based algorithm was established by an individual expert and was based on published and in-house results, independently from the data of the patients used in this evaluation. The predictive value of the algorithm for virological outcomes was retrospectively evaluated using the baseline genotype observed in patients on highly active antiretroviral therapy, failing virologically and subsequently starting a salvage regimen. METHODS: The independent association between the susceptibility score (calculated according to the algorithm) and the virological response at 3 months, was analysed using multivariable logistic regression and multiple linear regression models. RESULTS: In two clinical centres 240 patients were studied. At 3 months 35% had a viral load of <500 RNA copies/ml. Using multivariable logistic regression, the odds ratio of achieving a viral load <500 RNA copies/ml at month 3 per unit increase of susceptibility score was 2.0 (95% CI 1.3-3.1; P=0.002) after adjusting for baseline viral load, genotype-driven salvage therapy, number of new drugs in the regimen, use of a new drug class in the regimen, nelfinavir-containing salvage therapy and history of prior viral load <500 RNA copies/ml. Using multiple linear regression, the susceptibility score showed a significant linear correlation with the log viral load change (slope=-0.27 log10 RNA copies/ml; 95% CI -0.11 to -0.43; P=0.001) after adjusting for history of prior viral load <500 RNA copies/ml, number of new drugs in the salvage therapy, use of a new drug class in the salvage therapy and baseline viral load. CONCLUSIONS: This algorithm proved to be a significant independent predictor of therapy response at 3 months in this cohort of HIV-1-infected patients on salvage therapy. However, it should be subject to regular updates as is needed in this fast developing field.

Adolescent↗

PubMed2002

[Simulation study of the reconstruction algorithm for electrical impedance tomography based on the sensitivity theorem].

It is the intent of this paper to develop better reconstruction algorithm for electrical impedance tomography (EIT). Simulation study of the reconstruction algorithm based on the sensitivity theorem is made and the reconstruction algorithm is compared with other normal algorithms. The results indicate that sensitivity method as a kind of static reconstruction algorithm has higher accuracy and speed of iteration, so it is worth researching for laboratory modality work.

Algorithms↗

PubMed2002

[A treatment algorithm for developmental dysplasia of the hip for infants 0 to 18 months of age and its prospective results].

OBJECTIVES: We evaluated the results of treatment in patients who were treated according to an algorithm established for developmental dysplasia of the hip (DDH) during the first 18 months of life. METHODS: We developed an algorithm for DDH to be used in infants at 0 to 18 months of age. Patients who did not respond to, or who did not have the indication for, the use of Pavlik harness were treated according to our algorithm and evaluated prospectively. Thirty-three hips (24 patients; 21 girls, 3 boys; mean age 7.4 months; range 2.5 to 18 months) were followed-up for a mean of 42 months (range 15 to 90 months). Ultrasonographic evaluation was performed using the Graf method. Avascular necrosis was evaluated according to the Kalamchi and MacEwen classification, and radiological results according to the Severin classification. RESULTS: The mean acetabular index angles before and after treatment were 37.3 degrees (range 20 degrees to 58 degrees ) and 21.8 degrees (range 15 degrees to 30 degrees ), respectively. According to the Kalamchi and MacEwen classification, six hips (18.2%) had type I, three hips (9.1%) had type II, and one hip (3%) had type III avascular necrosis. According to the Severin criteria, 21 hips were considered in group I, 10 in group II, and two hips in group III. Acetabular osteotomies were performed in four hips. All patients had full range of motion without any pain and limp. CONCLUSION: Successful clinical results obtained in the hips treated according to this algorithm for DDH may serve to justify its use as a standard algorithm in the treatment of infants at ages 0 to 18 months.

Algorithms↗

PubMed1992

[Calculation algorithm of three-dimensional absorbed dose distribution due to in vivo administration of nuclides for radiotherapy].

In the in vivo administration of radionuclides for radiotherapy including radioimmunotherapy, an algorithm is proposed for the purpose of calculating three-dimensional absorbed dose distributions of tumors and adjacent tissues, and neighboring organs. The absorbed dose distribution due to the algorithm is given by convolution of the three-dimensional dose matrix for a unit cubic voxel containing unit cumulated activity, with the three-dimensional matrix of the cumulated activity distribution given by the same voxel size above. The dose calculation algorithm does not depend upon the source size, the source shape, and the nonuniform and irregular activity distribution. In addition, it can exceedingly decrease computation time compared to other calculation algorithms. Computer simulations were performed using the MIRD thyroid phantom for 32P, 90Y, 131I, 186Re, and 188Re that appear promising for radioimmunotherapy, and their results verified the validity of the proposed calculation algorithm and high accuracy of the calculations.

Algorithms↗

PubMed2004

A novel algorithm for scalable and accurate Bayesian network learning.

Bayesian Networks (BN) is a knowledge representation formalism that has been proven to be valuable in biomedicine for constructing decision support systems and for generating causal hypotheses from data. Given the emergence of datasets in medicine and biology with thousands of variables and that current algorithms do not scale more than a few hundred variables in practical domains, new efficient and accurate algorithms are needed to learn high quality BNs from data. We present a new algorithm called Max-Min Hill-Climbing (MMHC) that builds upon and improves the Sparse Candidate (SC) algorithm; a state-of-the-art algorithm that scales up to datasets involving hundreds of variables provided the generating networks are sparse. Compared to the SC, on a number of datasets from medicine and biology, (a) MMHC discovers BNs that are structurally closer to the data-generating BN, (b) the discovered networks are more probable given the data, (c) MMHC is computationally more efficient and scalable than SC, and (d) the generating networks are not required to be uniformly sparse nor is the user of MMHC required to guess correctly the network connectivity

Algorithms↗