Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Algorithms”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5Linked to original sources
PubMed1997

Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction.

This paper presents a new class of algorithms for penalized-likelihood reconstruction of attenuation maps from low-count transmission scans. We derive the algorithms by applying to the transmission log-likelihood a version of the convexity technique developed by De Pierro for emission tomography. The new class includes the single-coordinate ascent (SCA) algorithm and Lange's convex algorithm for transmission tomography as special cases. The new grouped-coordinate ascent (GCA) algorithms in the class overcome several limitations associated with previous algorithms. 1) Fewer exponentiations are required than in the transmission maximum likelihood-expectation maximization (ML-EM) algorithm or in the SCA algorithm. 2) The algorithms intrinsically accommodate nonnegativity constraints, unlike many gradient-based methods. 3) The algorithms are easily parallelizable, unlike the SCA algorithm and perhaps line-search algorithms. We show that the GCA algorithms converge faster than the SCA algorithm, even on conventional workstations. An example from a low-count positron emission tomography (PET) transmission scan illustrates the method.

Algorithms↗
PubMedDate not supplied

Iterative algebraic reconstruction algorithms for emission computed tomography: a unified framework and its application to positron emission tomography.

In this paper, a unified framework of iterative algebraic reconstruction for emission computed tomography (ECT) and its application to positron emission tomography (PET) is presented. The unified framework is based on an algebraic image restoration model and contains conventional iterative algebraic reconstruction algorithms: ART, SIRT, Landweber iteration (LWB), the generalized Landweber iteration (GLWB), the steepest descent method (STP), as well as iterative filtered backprojection (IFBP) reconstruction algorithms: Chang's method, Walters' method, and a modified iterative MAP. The framework provides an effective tool to systematically study conventional iterative algebraic algorithms and IFBP algorithms. Based on this framework, conventional iterative algebraic algorithms and IFBP algorithms are generalized. It is shown from the algebraic point of view that IFBP algorithms are not only excellent methods for correction of attenuation (either uniform or nonuniform) but are also good general iterative reconstruction algorithms (they can be applied to either attenuated or attenuation-free projections and converge very fast). The convergence behavior of iterative algebraic algorithms is discussed and insight is drawn into the fast convergence property of IFBP algorithms. A simulated PET system is used to evaluate IFBP algorithms and LWB in comparison with the maximum likelihood estimation via expectation maximization algorithm (MLE-EM) and the filtered backprojection (FBP) algorithm. The simulation results indicate that for both attenuation-free projection and attenuated projection cases IFBP algorithms have a significant computational advantage over LWB and MLE-EM, and have performance advantages over FBP in terms of contrast recovery and/or noise-to-signal ratios (NSRs) in regions of interest.

Algorithms↗
PubMed1986

Comparison of three algorithms used to evaluate adverse drug reactions.

The consistency of three algorithms in evaluating adverse drug reactions (ADRs) was studied. As part of a hospital's ADR protocol, doctor of pharmacy students were required to collect and summarize all ADR data. Algorithms by Kramer, Naranjo, and Jones were used to evaluate all ADRs between January and May 1984. Kramer's algorithm was used for every reported ADR; Naranjo's and Jones' algorithms were used to check consistency in scoring among ADRs already scored with the Kramer algorithm. The two numerical scales (Kramer and Naranjo) were compared using linear regression. The results of all three algorithms were translated into categories of suspicion (A = definite or probable; B = probable; C = possible; and D = unlikely, doubtful, or remote) and evaluated for consistency with a weighted kappa (kw) statistical test. A total of 28 ADRs were evaluated, and the correlation (r = 0.87) between the total numerical scores of the Kramer and Naranjo algorithms was significant. Comparison of the Kramer and Naranjo algorithms showed 67% agreement with a kw value of 0.43 (-1 = perfect disagreement and +1 = perfect agreement). Similarly, there was 67% agreement (kw = 0.48) between Kramer's algorithm and Jones' algorithm. Agreement between Naranjo's and Jones's algorithms was 64%, but the kw value was only 0.28. The simpler and less time-consuming Naranjo algorithm compared favorably with the Kramer algorithm in scoring ADRs; more data are needed to support the use of the Jones algorithm.

Drug-Related Side Effects and Adverse Reactions↗
PubMed2005

ROC-based assessments of 3D cortical surface-matching algorithms.

Algorithms for the semi-automated analysis of brain surfaces have recently received considerable attention, and yet, they rarely receive a rigorous assessment of their performance. We present a method for the quantitative assessment of performance across differing surface analysis algorithms and across various modifications of a single algorithm. The sensitivity and specificity of an algorithm for detecting known deformations added synthetically to the brains being studied are assessed using curves for Receiver Operating Characteristics (ROC). We also present a method for the isolation of sources of variance in MRI data sets that can contribute to degradation in performance of surface-matching algorithms. Isolation of these sources of variance allows determination of whether degradation in performance of surface-matching algorithms derives primarily from errors in registration of brains to a common coordinate space, from errors in placement of the known deformation, or from interindividual or between-group variability in morphology of the cortical surface. We apply these methods to the study of surface-matching algorithms that are based on fluid flow (FF) deformation, geodesic (GD) interpolation, or nearest neighbor (NN) proximity. We show that the performances of surface-matching algorithms depend on the presence of interindividual and between-group variability in the surfaces surrounding the cortical deformation. We also show that, in general, the FF algorithm performs as well as or better than the GD and NN algorithms. The large variance in identifying point correspondences across brain surfaces using the GD and the NN algorithms suggests strongly that these point correspondences are less valid than those determined by the FF algorithm. The GD and NN algorithms, moreover, are both vulnerable to detecting false-positive activations at points of high curvature, particularly along large fissures, cisterns, and cortical sulci.

Algorithms↗
PubMedDate not supplied

Statistical efficiency of adaptive algorithms.

The statistical efficiency of a learning algorithm applied to the adaptation of a given set of variable weights is defined as the ratio of the quality of the converged solution to the amount of data used in training the weights. Statistical efficiency is computed by averaging over an ensemble of learning experiences. A high quality solution is very close to optimal, while a low quality solution corresponds to noisy weights and less than optimal performance. In this work, two gradient descent adaptive algorithms are compared, the LMS algorithm and the LMS/Newton algorithm. LMS is simple and practical, and is used in many applications worldwide. LMS/Newton is based on Newton's method and the LMS algorithm. LMS/Newton is optimal in the least squares sense. It maximizes the quality of its adaptive solution while minimizing the use of training data. Many least squares adaptive algorithms have been devised over the years, but no other least squares algorithm can give better performance, on average, than LMS/Newton. LMS is easily implemented, but LMS/Newton, although of great mathematical interest, cannot be implemented in most practical applications. Because of its optimality, LMS/Newton serves as a benchmark for all least squares adaptive algorithms. The performances of LMS and LMS/Newton are compared, and it is found that under many circumstances, both algorithms provide equal performance. For example, when both algorithms are tested with statistically nonstationary input signals, their average performances are equal. When adapting with stationary input signals and with random initial conditions, their respective learning times are on average equal. However, under worst-case initial conditions, the learning time of LMS can be much greater than that of LMS/Newton, and this is the principal disadvantage of the LMS algorithm. But the strong points of LMS are ease of implementation and optimal performance under important practical conditions. For these reasons, the LMS algorithm has enjoyed very widespread application. It is used in almost every modem for channel equalization and echo cancelling. Furthermore, it is related to the famous backpropagation algorithm used for training neural networks.

Algorithms↗
PubMed2000

Validity of data-derived algorithms for ascertaining causes of adult death in two African sites using verbal autopsy.

background Verbal autopsy (VA) is used to ascertain causes of death using information obtained from bereaved relatives. Causes of death can be ascertained from VA questionnaires by a panel of physicians or from predefined algorithms. In a previous study, we developed data-derived algorithms using VA data from 796 adult deaths in hospitals in Tanzania, Ethiopia, and Ghana (primary sites). These computerized algorithms accurately estimated the cause-specific mortality fractions (CSMFs) for deaths due to injuries, meningitis, TB/AIDS and diarrhoeal diseases in the primary sites. Since the same data were used to generate and to validate the algorithms, the accuracy of our algorithms may have been overestimated. We report here on the validity of the algorithms when they were applied to VA data from two secondary sites in Ghana and Tanzania. Here, 'validity' is taken to mean the degree to which the algorithms replicated the physician-generated CSMF for major causes of death, when applied to the same VA data. methods VA interviews were conducted in two secondary sites: in Navrongo, Ghana, on 406 adult deaths, where three local physicians independently reviewed the questionnaires and assigned a cause of death. In Morogoro, Tanzania, VA interviews were conducted on 209 adult deaths, and a panel of physicians independently reviewed the VA questionnaires together with the hospital death certificates or hospital records to determine the cause of death. The CSMF obtained using each algorithm was compared with the CSMF obtained using physician review. results For injuries and meningitis, the algorithms and physician review estimated a similar CSMF in the Morogoro and Navrongo data. For TB/AIDS, the algorithm estimated a similar CSMF as the physicians in Morogoro. The algorithm for diarrhoeal diseases did not agree closely with the physicians in Morogoro or Navrongo. conclusions In general, our data-derived algorithms for assigning causes of death due to injuries, meningitis, and TB/AIDS estimated a similar CSMF as the physicians in the secondary sites. Recommendations for further validation and refinement are discussed. Computerized algorithms offer a potentially quick, affordable, and feasible method for assigning causes of death in mortality surveillance or studies using VA.

Adult↗
PubMed2002

Comparison of the performance of three diagnostic algorithms for regular broad complex tachycardia in practical application.

The authors previously proposed a Bayesian approach to the electrocardiographic diagnosis of regular broad complex tachycardia (BCT), which can be due to VT or supraventricular tachycardia with aberrant conduction (SVTAC). They also published an account comparing the theoretical merits in the design of two of the most commonly used diagnostic algorithms for the same purpose, those of Brugada et al. and Griffith et al. In this study, a direct head-to-head comparison was performed on the practical performances of the three algorithms in this study. A set of 111 ECGs showing regular BCT (77 VT, 34 SVTAC) whose diagnoses were confirmed by electrophysiological study was shown to five internists in general medicine at a district general hospital. The observers were asked to comment on whether the ECG criteria in the three algorithms tested were fulfilled or not, and a computer program then derived the corresponding diagnoses. The sensitivity and specificity for VT achieved by the Brugada algorithm were 92% and 44%, 92% and 44% by the Griffith algorithm, and 97% and 56% by the Bayesian algorithm. The Bayesian algorithm achieved a higher sensitivity and specificity than the other two algorithms, but the differences are not statistically significant (P = 0.6583 and P = 0.5334, respectively). The Brugada, Griffith, and Bayesian algorithms show comparable performances in terms of overall sensitivity and specificity when tested in practice. Of the three algorithms, the Griffith algorithm excels in simplicity and is the easiest to implement in practice. The Bayesian algorithm achieved slightly higher values for sensitivity and specificity than the Brugada and Griffith algorithms but may be more suitable for automated computer-aided diagnosis of ECG due to its complexity.

Algorithms↗
PubMed2006

View-independent reconstruction algorithms for cone beam CT with general saddle trajectory.

In Yang et al (2006 Phys. Med. Biol. 51 1157-72), an exact filtered backprojection (FBP) reconstruction algorithm was proposed for cone beam tomography with saddle trajectory based on the seminal works of Pack and Noo (2005a Inverse Problems 21 1105-20; 2005b 8th Int. Meeting on Fully 3D Reconstruction in Radiology and Nuclear Medicine (Salt Lake City) ed F Noo, H Kudo and L G Zeng pp 287-90). However, the artefacts due to discretization and/or sampling errors in the reconstructed images by this method were still visible, especially when the pitch is large. In this paper, two view-independent (VI) algorithms, which are similar to the FDK-type algorithms (Feldkamp et al 1984 J. Opt. Soc. Am. A 1 612-19), are proposed for planar detector geometry. The first VI algorithm involves two filtered projections and a small additional term (two-dimensional (2D) Radon transform term). One of the filtered projections is obtained by ramp filtering (as in the FDK algorithm for circular trajectory) and the other one is obtained by Hilbert transform. The 2D Radon transform term is just like the term which was first derived by Hu (1996 Scanning 18 572-81) for a circular trajectory. The second VI algorithm involves only one filtered projection term, which is obtained by differentiation followed by Hilbert transform and the 2D Radon transform term. Both algorithms involve only one backprojection step with a weighting factor as in the FDK algorithm. The simulation studies show that the pixel values of the reconstructed images by the VI algorithms are more accurate than those by the original view differencing (VD) algorithm, the streak artefacts are also reduced, and their computational times are comparable to that of the original VD algorithm. We also generalize the concept of saddle trajectory and the corresponding reconstruction algorithm. The generalized algorithm is also theoretically exact, has a shift-invariant FBP structure, and does not depend on the concept of pi-line.

Algorithms↗
PubMed1999

Implementation of probabilistic decision rules improves the predictive values of algorithms in the diagnostic management of ectopic pregnancy.

Current algorithms for the diagnosis of ectopic pregnancy do not take into account the heterogeneity in patient profiles. Such heterogeneity can lead to differences in the pre-test probability of ectopic pregnancy. In patients with clinical symptoms, for example, the probability of presence of an ectopic pregnancy is higher than in symptom-free patients. Any additional tests should then be interpreted differently, depending on the pre-test probability. We present a diagnostic algorithm that uses probabilistic decision rules for the evaluation of women with suspected ectopic pregnancy with flexible cut-off levels for test positivity We compare it with a general algorithm that uses fixed cut-off levels. Fictitious cohorts, varying in prevalence of ectopic pregnancy were put together, using data obtained from a cohort of >800 women with suspected ectopic pregnancy. In the inflexible algorithm, ectopic pregnancy was diagnosed whenever it could be visualized at transvaginal sonography, or where serum human chorionic gonadotrophin (HCG) exceeded a rigid cut-off level; ectopic pregnancy was rejected if an intrauterine pregnancy was seen or when serum HCG decreased. In the flexible algorithm, a post-test probability was obtained after each test, using pre-test probabilities and test-based likelihood ratios. Ectopic pregnancy was diagnosed whenever the post-test probability for ectopic pregnancy exceeded 95%, whereas this diagnosis was rejected if the calculated post-test probability fell below 1%. For both algorithms, sensitivity and specificity as well as predictive values were calculated. At each prevalence, the inflexible algorithm was associated with a sensitivity of 93% and a specificity of 97%. In contrast, the sensitivity and specificity of the flexible, individualized algorithm depended on the prevalence of ectopic pregnancy. Consequently, predictive values varied strongly when the inflexible algorithm was used, whereas they were much more stable after using the flexible algorithm. For five possible valuations of false positive and false negative diagnoses, the flexible algorithm reduced the expected disutility, compared with the inflexible algorithm. It is concluded that clinicians should incorporate probabilistic decision rules in algorithms used for the diagnosis of ectopic pregnancy.

Algorithms↗
PubMed2005

Evaluation of a particle swarm algorithm for biomechanical optimization.

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can be affected by scaling to account for design variables with different length scales or units. In this study we evaluate a recently-developed version of the particle swarm optimization (PSO) algorithm to address these problems. The algorithm's global search capabilities were investigated using a suite of difficult analytical test problems, while its scale-independent nature was proven mathematically and verified using a biomechanical test problem. For comparison, all test problems were also solved with three off-the-shelf optimization algorithms--a global genetic algorithm (GA) and multistart gradient-based sequential quadratic programming (SQP) and quasi-Newton (BFGS) algorithms. For the analytical test problems, only the PSO algorithm was successful on the majority of the problems. When compared to previously published results for the same problems, PSO was more robust than a global simulated annealing algorithm but less robust than a different, more complex genetic algorithm. For the biomechanical test problem, only the PSO algorithm was insensitive to design variable scaling, with the GA algorithm being mildly sensitive and the SQP and BFGS algorithms being highly sensitive. The proposed PSO algorithm provides a new off-the-shelf global optimization option for difficult biomechanical problems, especially those utilizing design variables with different length scales or units.

Algorithms↗
PubMed2002

A leaf sequencing algorithm to enlarge treatment field length in IMRT.

With MLC-based IMRT, the maximum usable field size is often smaller than the maximum field size for conventional treatments. This is due to the constraints of the overtravel distances of MLC leaves and/or jaws. Using a new leaf sequencing algorithm, the usable IMRT field length (perpendicular to the MLC motion) can be mostly made equal to the full length of the MLC field without violating the upper jaw overtravel limit. For any given intensity pattern, a criterion was proposed to assess whether an intensity pattern can be delivered without violation of the jaw position constraints. If the criterion is met, the new algorithm will consider the jaw position constraints during the segmentation for the step and shoot delivery method. The strategy employed by the algorithm is to connect the intensity elements outside the jaw overtravel limits with those inside the jaw overtravel limits. Several methods were used to establish these connections during segmentation by modifying a previously published algorithm (areal algorithm), including changing the intensity level, alternating the leaf-sequencing direction, or limiting the segment field size. The algorithm was tested with 1000 random intensity patterns with dimensions of 21 x 27 cm2, 800 intensity patterns with higher intensity outside the jaw overtravel limit, and three different types of clinical treatment plans that were undeliverable using a segmentation method from a commercial treatment planning system. The new algorithm achieved a success rate of 100% with these test patterns. For the 1,000 random patterns, the new algorithm yields a similar average number of segments of 36.9 +/- 2.9 in comparison to 36.6 +/- 1.3 when using the areal algorithm. For the 800 patterns with higher intensities outside the jaw overtravel limits, the new algorithm results in an increase of 25% in the average number of segments compared to the areal algorithm. However, the areal algorithm fails to create deliverable segments for 90% of these patterns. Using a single isocenter, the new algorithm provides a solution to extend the usable IMRT field length from 21 to 27 cm for IMRT on a commercial linear accelerator using the step and shoot delivery method.

Algorithms↗
PubMed2006

EMD: an ensemble algorithm for discovering regulatory motifs in DNA sequences.

BACKGROUND: Understanding gene regulatory networks has become one of the central research problems in bioinformatics. More than thirty algorithms have been proposed to identify DNA regulatory sites during the past thirty years. However, the prediction accuracy of these algorithms is still quite low. Ensemble algorithms have emerged as an effective strategy in bioinformatics for improving the prediction accuracy by exploiting the synergetic prediction capability of multiple algorithms. RESULTS: We proposed a novel clustering-based ensemble algorithm named EMD for de novo motif discovery by combining multiple predictions from multiple runs of one or more base component algorithms. The ensemble approach is applied to the motif discovery problem for the first time. The algorithm is tested on a benchmark dataset generated from E. coli RegulonDB. The EMD algorithm has achieved 22.4% improvement in terms of the nucleotide level prediction accuracy over the best stand-alone component algorithm. The advantage of the EMD algorithm is more significant for shorter input sequences, but most importantly, it always outperforms or at least stays at the same performance level of the stand-alone component algorithms even for longer sequences. CONCLUSION: We proposed an ensemble approach for the motif discovery problem by taking advantage of the availability of a large number of motif discovery programs. We have shown that the ensemble approach is an effective strategy for improving both sensitivity and specificity, thus the accuracy of the prediction. The advantage of the EMD algorithm is its flexibility in the sense that a new powerful algorithm can be easily added to the system.

Algorithms↗
PubMed2005

Improvement of glycemic control in subjects with poorly controlled type 2 diabetes: comparison of two treatment algorithms using insulin glargine.

OBJECTIVE: Large prospective studies have demonstrated that optimum glycemic control is not routinely achieved in clinical practice. Barriers to optimal insulin therapy include hypoglycemia, weight gain, and suboptimal initiation and dose titration. This study compared two treatment algorithms for insulin glargine initiation and titration: algorithm 1 (investigator led) versus algorithm 2 (performed by study subjects). RESEARCH DESIGN AND METHODS: A prospective, multicenter (n = 611), multinational (n = 59), open-label, 24-week randomized trial in 4,961 (algorithm 1, n = 2,493; algorithm 2, n = 2,468) suboptimally controlled type 2 diabetic subjects. RESULTS: At baseline, mean diabetes duration was 12.3 +/- 7.2 years, and 72% of subjects were pretreated with insulin. At end point, there was no significant difference in the incidence of severe hypoglycemia between algorithms 1 and 2 (0.9 vs. 1.1%). There was a significant reduction in HbA(1c) from 8.9 +/- 1.3 to 7.8 +/- 1.2%, with a greater decrease (P < 0.001) with algorithm 2 (-1.22%) versus algorithm 1 (-1.08%). Fasting blood glucose decreased from 170 to 110 mg/dl, with a greater decrease (P < 0.001) with algorithm 2 (-62 mg/dl) versus algorithm 1 (-57 mg/dl). Mean basal insulin dose increased from 22.9 +/- 15.5 to 43.0 +/- 25.5 IU, with a significant difference (P < 0.003) between algorithm 2 (21.6 IU) and algorithm 1 (18.7 IU). CONCLUSIONS: Glargine is safe and effective in improving glycemic control in a large, diverse population with longstanding type 2 diabetes. A simple subject-administered titration algorithm conferred significantly improved glycemic control with a low incidence of severe hypoglycemia compared with physician-managed titration.

Algorithms↗
PubMed1998

Evaluation of clinical algorithms for the diagnosis of gonococcal and chlamydial infections among men with urethral discharge or dysuria and women with vaginal discharge in Benin.

OBJECTIVE: To evaluate the validity of clinical algorithms proposed in Benin for the diagnosis of gonococcal or chlamydial infections among men with urethral discharge or dysuria and women with vaginal discharge consulting health services in Benin. These algorithms were adapted from those proposed by the World Health Organisation. METHODS: Consecutive patients with these symptoms were enrolled at three primary healthcare centres. The reference test for gonorrhoea was a combination of results from culture and polymerase chain reaction and chlamydial infection was ascertained by enzyme linked immunosorbent assay and PCR. In women, two algorithms were evaluated, one based on symptoms and risk assessment (algorithm A), the other relying also on speculum examination (algorithm B). The first algorithm evaluated in men relied on clinical examination only (algorithm C) whereas the other used microscopic examination of urethral smears (algorithm D). Sensitivity, specificity, and positive and negative predictive values of these algorithms were assessed using standard methods. RESULTS: In 192 women, the prevalence of gonococcal and chlamydial infections was 5.7% and 2.1% respectively (combined prevalence of 7.8%). The sensitivity, specificity, positive and negative predictive values of algorithm A (algorithm B) were respectively 86.7% (93.3%), 41.8% (34.5%), 11.2% (10.8%), and 97.4% (98.4%). In 105 men, the corresponding prevalences were 39.0% and 7.6% respectively (for a combined prevalence of 44.8%). The sensitivity, specificity, positive and negative predictive values of algorithm C (algorithm D) were respectively 91.5% (87.2%), 60.3% (67.2%), 65.2% (68.3%), and 89.7% (86.7%). CONCLUSION: A syndromic approach for the diagnosis of urethritis in men appears appropriate. In women, the diagnosis of gonococcal or chlamydial infection without specific laboratory tests, which are not easily affordable in developing countries, remains highly problematic.

Adult↗
PubMed1998

Risk assessment, symptoms, and signs as predictors of vulvovaginal and cervical infections in an urban US STD clinic: implications for use of STD algorithms.

OBJECTIVE: To identify clinical epidemiological correlates of cervical and vaginal infections and assess alternative algorithms, including two new reproductive tract infection (RTI) algorithms, for syndromic management of these infections. DESIGN, SETTING AND SUBJECTS: We prospectively studied clinical manifestations and risk correlates of cervical and vaginal infections in a randomly sampled group of 779 female patients seeking evaluation for a new problem at a Seattle STD clinic. METHODS: One experienced clinician performed standardised history, physical examination, and microscopy. Reference laboratories performed microbiological tests. Three levels of retrospective evaluation of algorithms included risk assessment and symptom review (RAS) alone; addition of speculum and bimanual examinations; and further addition of microscopy. RESULTS: (1) Chief complaint of abnormal vaginal discharge predicted a significantly lower rate of gonorrhoea (GC) or chlamydial infection (CT) than rates observed with no complaint of vaginal discharge. Only the elicited symptom of yellow vaginal discharge (not the more common symptoms of increased or malodorous vaginal discharge) predicted GC or CT. Chief complaint of abnormal vaginal discharge itself predicted trichomoniasis (TV) and bacterial vaginosis (BV), not cervical infection. Candida albicans was strongly associated with the chief complaint of vulvar pruritus, not with the chief complaint of abnormal vaginal discharge. (2) Applying these algorithms in STD clinics only to women with the chief complaint of abnormal vaginal discharge, rather than to all women, decreases sensitivity for GC or CT, without increasing positive predictive value (PPV). Criteria for inclusion of patients have more effect on the performance of these algorithms than do the levels of evaluation used. (3) A modified World Health Organisation (WHO) algorithm applied only to patients with symptoms of vaginal discharge, involving treatment of RAS positives for cervical infection, followed by treatment of vaginal infections and cervicitis based on examination of RAS negatives and positives, had a sensitivity of 50% and PPV of 33% for cervical infection, and very low sensitivity for BV, TV, and for vulvovaginal candidiasis (VVC). (4) An RTI algorithm derived from these data, and applied to all STD patients, involving RAS and examination of all RAS negatives, provided treatment to all cases of BV and TV associated with symptoms of vaginal discharge; treatment of all VVC associated with symptoms of vulvar pruritus; treatment for GC and GT to all RAS positives (using easily elicited risk factors) and to RAS negatives with signs of cervicitis or PID. This algorithm had a sensitivity of 87% and a PPV of 33% for GC or CT in this population, with its 24% prevalence of GC or CT. The sensitivity for BV, TV, and VVC greatly exceeded that of the modified WHO algorithm. (5) A modified RTI algorithm, involving examination rather than treatment of RAS positive women, no examination of RAS negatives, decreased the sensitivity for cervical infection to 55% but increased the PPV to 51%. CONCLUSIONS: Syndromic management of vaginal discharge offers relief of symptoms, prevention of transmission of trichomonas, and perhaps prevention of complications of BV. The 51% PPV of the modified RTI algorithm probably would warrant treatment and partner notification for GC and CT in settings with similar rates of GC and CT where more specific tests are lacking. However, as the prevalence of GC or CT decreases, the ratio of uninfected to infected who receive treatment with these algorithms would increase greatly, making the algorithms potential victims of their own success.

Adult↗
PubMed2002

Generating longitudinal screening algorithms using novel biomarkers for disease.

Recent advances in molecular technology are leading to the discovery of new tumor biomarkers that may be useful for cancer screening and early diagnosis. Translating a potential screening biomarker from the laboratory to its use in patient care may require an algorithm or screening rule for its application. An algorithm that can detect the smallest deviation from a defined norm is likely to achieve the highest sensitivity, but any practical screening algorithm must do so with strict controls on test specificity to avoid false-positive results, and unnecessary patient alarm and risk. Longitudinal algorithms that make use of previous tumor marker values and trends are likely to obtain improvements over single threshold rules. Thus far, a few longitudinal screening algorithms have been proposed (e.g., using serial prostate-specific antigen values for the detection of prostate cancer and serial CA125 values for the detection of ovarian cancer), but these algorithms are not appropriate for novel tumor marker discoveries, because they rely on unverifiable assumptions that may not translate to the behavior of the new marker. The algorithm presented here is motivated by: (a) the need to develop an algorithm for early detection using novel markers; (b) the practical demands on data and specimen availability; and (c) the need to be robust enough to accommodate a wide range of tumor growth behavior. We use Parametric Empirical Bayes statistical theory to model the trajectory of markers over time in a cohort of asymptomatic healthy subjects, and use the estimated trajectory to produce person-specific thresholds that depend on the screening history of each person. The thresholds are chosen to give the person (or population) a specified false-positive rate. The resulting algorithm is simple and can be represented in a simple graph or a chart. The statistical analysis needed to generate the algorithm can be found in nearly every basic statistical package. The algorithm is highly robust and can detect a wide range of tumor behaviors. The Parametric Empirical Bayes screening algorithm should take a central role when evaluating marker discoveries for use in screening. The algorithm is particularly useful when screening with a new marker of which the behavior in the preclinical period is not well known.

Algorithms↗
PubMed1983

Clinical trial of an emergency resuscitation algorithm.

Clinical trials of a resuscitation algorithm for patients entering the Surgical Emergency Department (ED) with acute hypotension were conducted for a 30-month period. The intent was not to compare good management with bad, but rather university-run county hospital services with and without an algorithm. The study group was comprised of 603 hypotensive patients out of 6833 consecutive admissions. The effects of the policy of using a resuscitation algorithm were evaluated by the outcomes of the patients who were treated by residents given the algorithm (protocol group) versus those treated by residents not given the algorithm (control group). The efficacy of the algorithm, per se, was evaluated by outcomes of patients whose management was in satisfactory compliance with the algorithm as compared with those whose management deviated from the algorithm. The patients were also evaluated by the primary cause of their hypotension and the presence of severe associated illnesses. Outcomes of patients treated by residents given the algorithm were as good and in a number of respects better than those of patients treated by residents without the algorithm. The mean resuscitation time of the protocol group was markedly and significantly less than that of the control group indicating that the policy of using the algorithm facilitated resuscitation even though it was not always properly followed. Patients with trauma, hemorrhage, and sepsis, whose care was in satisfactory compliance with the algorithm had shorter resuscitation times, lower MAP-time deficits, and less shock-related complications. The algorithm which is primarily directed toward fluid resuscitation did not appear to be efficacious for patients whose trauma was primarily head injury, where fluid restriction may be the therapy of choice.

Adolescent↗
PubMed2000

Automatic quantification of defect size using normal templates: a comparative clinical study of three commercially available algorithms.

Infarct size assessed by myocardial single-photon emission tomography (SPET) imaging is an important prognostic parameter after myocardial infarction (MI). We compared three commercially available automatic quantification algorithms that make use of normal templates for the evaluation of infarct extent and severity in a large population of patients with remote MI. We studied 100 consecutive patients (80 men, mean age 63 +/- 11 years, mean LVEF 47% +/- 15%) with a remote MI who underwent resting technetium-99m tetrofosmin gated SPET study for infarct extent and severity quantification. The quantification algorithms used for comparison were a short-axis algorithm (Cedars-Emory quantitative analysis software, CEqual), a vertical long-axis algorithm (VLAX) and a three-dimensional fitting algorithm (Perfit). Semiquantitative visual infarct extent and severity assessment using a 20-segment model with a 5-point score and the relation of infarct extent and severity with rest LVEF determined by quantitative gated SPET (QGS) were used as standards to compare the different algorithms. Mean infarct extent was similar for visual analysis (30% +/- 21%) and the VLAX algorithm (25% +/- 17%), but CEqual (15% +/- 11%) and Perfit (5% +/- 6%) mean infarct extents were significantly lower compared with visual analysis and the VLAX algorithm. Moreover, infarct extent determined by Perfit was significantly lower than infarct extent determined by CEqual. Correlations between automatic and visual infarct extent and severity evaluations were moderate (r = 0.47, P < 0.0001 to r = 0.62, P < 0.0001) but comparable for all three algorithms. Correlations between LVEF and visual evaluation of infarct extent (r = -0.80, P < 0.0001) and severity (r = -0.82, P < 0.0001) were good but correlations were significantly lower for all three algorithms (r = -0.48, P < 0.0001 to r = -0.65, P < 0.0001). Systematically lower correlations were found in non-anterior infarctions (n = 69) and obese patients (BMI > or = 30 kg/m2, n = 32) compared with anterior infarctions and non-obese patients for all three algorithms. In this large series of post-MI patients, results of infarct extent and severity determination by automatic quantification algorithms that make use of normal templates were not interchangeable and correlated only moderately with semiquantitative visual analysis and LVEF.

Adult↗