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PubMed1999

Using wound care algorithms: a content validation study.

PURPOSE: Valid and reliable heuristic devices facilitating optimal wound care are lacking. The objectives of this study were to establish content validation data for a set of wound care algorithms, to identify their associated strengths and weaknesses, and to gain insight into the wound care decision-making process. METHODS: Forty-four registered nurse wound care experts were surveyed and interviewed at national and regional educational meetings. Using a cross-sectional study design and an 83-item, 4-point Likert-type scale, this purposive sample was asked to quantify the degree of validity of the algorithms' decisions and components. Participants' comments were tape-recorded, transcribed, and themes were derived. RESULTS: On a scale of 1 to 4, the mean score of the entire instrument was 3.47 (SD +/- 0.87), the instrument's Content Validity Index was 0.86, and the individual Content Validity Index of 34 of 44 participants was > 0.8. Item scores were lower for those related to packing deep wounds (P < .001). No other significant differences were observed. Qualitative data analysis revealed themes of difficulty associated with wound assessment and care issues, that is, the absence of valid and reliable definitions. CONCLUSION: The wound care algorithms studied proved valid. However, the lack of valid and reliable wound assessment and care definitions hinders optimal use of these instruments. Further research documenting their clinical use is warranted. Research-based practice recommendations should direct the development of future valid and reliable algorithms designed to help nurses provide optimal wound care.

Adult↗

PubMed1998

Algorithm for the diagnosis and management of asthma: a practice parameter update: Joint Task Force on Practice Parameters, representing the American Academy of Allergy, Asthma and Immunology, the American College of Allergy, Asthma and Immunology, and the Joint Council of Allergy, Asthma and Immunology.

This algorithm on the diagnosis and treatment of asthma is intended to complement and update the previously published Practice Parameters for the Diagnosis and Treatment of Asthma. Both documents were developed by the Joint Task Force on Practice Parameters, representing the AAAAI, ACAAI, and the JCAAI. The authors of this asthma algorithm have attempted to include all the elements essential for the diagnosis and care of patients with asthma. Every effort was made to keep the algorithm clear and concise, yet thorough and complete (Fig 1). Each component of the algorithm is elaborated further in a brief annotation. For further discussion, the reader is referred to the more extensive Practice Parameters for the Diagnosis and Treatment of Asthma.

Acute Disease↗

PubMed2003

An efficient peak assignment algorithm for two-dimensional NMR correlation spectra of framework structures.

An algorithm is described for efficiently assigning the resonances in NMR spectra to the inequivalent atoms in the structure under study based on the information in two-dimensional NMR correlation experiments and the 'connectivities' known from the structure. The algorithm, which is based on basic graph theory concepts, finds all possible assignments sets which are consistent with the experimentally observed correlations and known connectivities in a very efficient manner. It is designed to deal with less than ideal experimental data in which there may be overlapping peaks and uncertainty about the presence or absence of correlation peaks. The algorithm was primarily developed for assigning the peaks in the high-resolution solid-state 29Si MAS NMR spectra of highly siliceous zeolites based on two-dimensional 29Si INADEQUATE spectra and is described using the zeolites ZSM-12 and ZSM-5 as working examples. Peak assignment for zeolite frameworks is particularly challenging since there is often little or no information to distinguish peaks from one another such as characteristic chemical shifts, relative intensities, or different relaxation times. The algorithm may be a useful tool for easily, reliably, and efficiently working out peak assignments from other types of correlation experiments on other types of systems and further examples are provided in the Supplementary material.

Algorithms↗

PubMed1997

Computer prediction of adaptive bone remodelling around noncemented femoral prostheses: the relationship between damage-based and strain-based algorithms.

Several mathematical models to predict tissue adaptation have been derived since Julius Wolff proposed a function-form relationship for bone. These can be formulated as computational procedures (algorithms) to predict bone adaptation around implants. The objective of this paper was to further develop the damage-adaptive algorithm, to test its validity, and to determine the relationship between it and algorithms based on strain energy. This was achieved using finite element models of the proximal femur, one for the intact case and another for the case where a noncemented hip prosthesis is implanted. The finite models were generated using CT scan data. Initial bone resorption patterns around a femoral prosthesis following total hip arthroplasty were computed for both damage-adaptive and strain-adaptive adaptation rules. It is found that the damage-adaptive algorithm can successfully predict the bone's adaptive behaviour in response to altered mechanical loading provided that account is taken of the nonlinear nature of damage accumulation. Predictions are made using a strain energy stimulus for comparison with the damage stimulus, and a theoretical relationship between the two is proposed. It is shown that an advantage of the damage approach over the strain-based approach is that the nonlinearity required to replicate clinically observed resorption patterns can be derived theoretically, whereas for strain-adaptive remodelling, empirical relationships are assumed.

Adaptation, Physiological↗

PubMed2002

Algorithmic tools for real-time microsurgery simulation.

Today, there is growing interest in computer surgical simulation to enhance surgeons' training. This paper presents a simulation system based on novel algorithms for animating instruments interacting with deformable tissue in real-time. The focus is on computing the deformation of a tissue subject to external forces, and detecting collisions among deformable and rigid objects. To achieve real-time performance, the algorithms take advantage of several characteristics of surgical training: (1) visual realism is more important than accurate, patient-specific simulation; (2) most tissue deformations are local; (3) human-body tissues are well damped; and (4) surgical instruments have relatively slow motions. Each key algorithm is described in detail and quantitative performance-evaluation results are given. The specific application considered in this paper is microsurgery, in which the user repairs a virtual severed blood vessel using forceps and a suture (micro-anastomosis). Microsurgery makes it possible to demonstrate several facets of the simulation algorithms, including the deformations of the blood vessel and the suture, and the collisions and interactions between the vessel, the forceps, and the suture. Validation of the overall microsurgery system is based on subjective analysis of the simulation's visual realism by different users.

Algorithms↗

PubMed2000

Transferability of neural network-based decision support algorithms for early assessment of chest-pain patients.

The present investigation concerns methodological and epidemiological aspects of the transferability of artificial neural network-based algorithms, as key-components for classification in decision support systems (DSS). The prevalence of pathological conditions to be detected must be known in order to tune an artificial neural networks (ANN)-decision algorithm so that the predictive values of the outcome fulfil medical requirements. Another aspect of transferability, when clinical laboratory results are used, concerns differences in analytical performance of measuring instruments. The relative bias between two instruments is not known exactly, but must be estimated and corrected for. A general method, based on original measured data sets and statistical modeling, was developed for simulating the impact of various correction procedures when using different analytical instruments. The simulation methodology was applied to a real clinical problem of ruling-in/ruling-out of patients with suspected acute myocardial infarction (AMI) by biochemical monitoring. The recommended correction procedure was based on method comparison with use of five duplicate measurements on a common set of patient samples covering the relevant measuring interval. Transferability of laboratory data over time was also studied. The design of quality assurance procedures should be based on analytical quality requirement specifications related to medical needs. Limits of critically sized systematic errors were assessed by calculating the decrease in diagnostic performance of the ANN-algorithm as a result of temporary analytical disturbances. The consequences for the design of QA procedures was illustrated. It is concluded that the actual ANN-decision algorithm for early assessment of chest-pain patients should be possible to transfer to new sites under realistic conditions.

Algorithms↗

PubMed2003

A chaotic approach to maintain the population diversity of genetic algorithm in network training.

The concept of chaos being radically different from statistical randomness is introduced into chemometrics research. The chaotic system that is deterministic with underlying patterns and inherent ability in searching the space of interest has been employed to improve the performance of chemometric algorithms. In this paper, a chaotic mutation is introduced into the genetic algorithm (GA) which is used for artificial neural network (ANN) training. The chaotic algorithm is very efficient in maintaining the population diversity during the evolution process of GA. The proposed algorithm CGANN has been testified by prediction of vibrational frequencies of octahedral hexahalides from some selected molecular parameters.

Algorithms↗

PubMed2005

The role of diagnostic algorithms in the management of blunt splenic injury.

BACKGROUND: Diagnostic algorithms for patients with blunt abdominal trauma have been in use since 1995. This study investigated the role of diagnostic algorithms in the management of adult patients with blunt splenic injury at our institution. METHODS: A retrospective review of hospital records was performed to enroll patients with blunt injury of the spleen. Demographic data and information about injury severity, diagnostic methods, management and final outcomes were evaluated. Patients were separated into an early and late group according to the year that diagnostic algorithms were used (1990-1994 or 1995-1999). RESULTS: One hundred and twenty-one patients were enrolled. Initially, 71 patients had an operation (OP group), whereas 50 received non-operative management (NOM group). Patients in the OP versus NOM group had lower blood pressure and greater transfusion volumes in the emergency room, higher grade splenic injury, and a greater rate of intra-abdominal-related injury. NOM failed in 7 patients (14%). Early- versus late-group patients were less likely to have NOM and high grade splenic injury; however, the rate of NOM failure was not different between the early and late groups. CONCLUSION: Diagnostic algorithms using sonograms for screening provide an initial means of selecting patients for NOM. Patients with higher grades of splenic injury can then be managed non-operatively.

Adolescent↗

PubMed2002

Calibration standardization algorithm for partial least-squares regression: application to the determination of physiological levels of glucose by near-infrared spectroscopy.

Calibration standardization methodology for near-infrared (near-IR) spectroscopy is described for updating a partial least-squares calibration model to take into account changes in instrumental response. The guided model reoptimization (GMR) algorithm uses a transfer set of eight samples to characterize the new response and a database of previously acquired spectra used to develop the original calibration model. The samples in the transfer set need not have been measured under the old instrumental conditions, making the algorithm compatible with samples that change over time. The spectra comprising the transfer set are used to guide an iterative optimization procedure that (1) finds an optimal subset of samples from the original database to use in computing the updated model and (2) finds an optimal set of weights to apply to the spectral resolution elements in order to minimize the effects of instrumental changes on the computed model. The optimization relies on an alternating grid search and stepwise addition/deletion steps. The algorithm is evaluated through the use of combination region near-IR spectra to determine physiological levels of glucose in a synthetic biological matrix containing bovine serum albumin and triacetin in phosphate buffer. The ability to update a calibration to account for changes in the response of a Fourier transform spectrometer over four to six years is examined in this study. Separate spectral databases collected in 1994 and 1996 are used with a transfer set and separate test set of spectra collected in 2000. With the 1994 database, the standardization algorithm achieves a standard error of prediction (SEP) of 0.69 mM for the 2000 test set. This compares favorably to SEP values > 2 mM when the original 1994 calibration model is used without standardization. A similar improvement in the prediction performance of the 2000 test set is obtained after standardization with the 1996 database (SEP = 0.70 mM).

Algorithms↗

PubMed2005

Congruent strategies for carbohydrate sequencing. 3. OSCAR: an algorithm for assigning oligosaccharide topology from MSn data.

This is the third in a sequence of reports devoted to the development of congruent strategies for carbohydrate sequencing. Two previous reports outlined the strategies for observing structural detail from MSn data and introduced tools that compile, search, and compare fragment spectra in a bottom-up approach to oligosaccharide sequencing. In this third report, we introduce the operational details of an algorithm that we define as the Oligosaccharide Subtree Constraint Algorithm (OSCAR). This algorithm assimilates analyst-selected MSn ion fragmentation pathways into oligosaccharide topology (branching and linkage) using what may be considered a top-down sequencing strategy. Guided by a series of logical constraints, this de novo algorithm provides molecular topology without presumed biosynthetic constraints or external comparisons. In this introductory study, OSCAR is applied to a series of permethylated oligomers and isomeric glycans, and topologies are assigned in a few hundredths of a second.

Algorithms↗

PubMed1998

Automation of data collection for matrix-assisted laser desorption/ionization mass spectrometry using a correlative analysis algorithm.

Automation of data collection in matrix-assisted laser desorption/ionization (MALDI) mass spectrometry using a correlative analysis algorithm is demonstrated. This algorithm was employed to compensate for mass spectral jittering in MALDI data collection (e.g., peak shifts along the m/z axis, signal intensity deviations, etc.). Several important parameters for performing correlative analysis, such as the minimum correlation coefficient to be used and number of mass spectra to acquire prior to correlation, have been investigated and optimized. In addition, the correlation algorithm improved mass resolution of low- and high-molecular-weight compounds by as much as a factor of 4. Signal reproducibility in MALDI quantitative analysis also is improved when correlation is employed for data collection. This data collection algorithm can be used in conjunction with other instrumental optimization programs to allow for fully automated MALDI analysis, which is required for the routine applications carried out in many analytical laboratories.

Algorithms↗

PubMed2000

An algorithm for automated bacterial identification using matrix-assisted laser desorption/ionization mass spectrometry.

An algorithm for bacterial identification using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry is being developed. This mass spectral fingerprint comparison algorithm is fully automated and statistically based, providing objective analysis of samples to be identified. Based on extraction of reference fingerprint ions from test spectra, this approach should lend itself well to real-world applications where samples are likely to be impure. This algorithm is illustrated using a blind study. In the study, MALDI-MS fingerprints for Bacillus atrophaeus ATCC 49337, Bacillus cereus ATCC 14579T, Escherichia coli ATCC 33694, Pantoea agglomerans ATCC 33243, and Pseudomonas putida F1 are collected and form a reference library. The identification of test samples containing one or more reference bacteria, potentially mixed with one species not in the library (Shewanella alga BrY), is performed by comparison to the reference library with a calculated degree of association. Out of 60 samples, no false positives are present, and the correct identification rate is 75%. Missed identifications are largely due to a weak B. cereus signal in the bacterial mixtures. Potential modifications to the algorithm are presented and result in a higher than 90% correct identification rate for the blind study data, suggesting that this approach has the potential for reliable and accurate automated data analysis of MALDI-MS.

Algorithms↗

PubMed1991

New joint prediction algorithm (Q7-JASEP) improves the prediction of protein secondary structure.

The classical problem of secondary structure prediction is approached by a new joint algorithm (Q7-JASEP) that combines the best aspects of six different methods. The algorithm includes the statistical methods of Chou-Fasman, Nagano, and Burgess-Ponnuswamy-Scheraga, the homology method of Nishikawa, the information theory method of Garnier-Osgurthope-Robson, and the artificial neural network approach of Qian-Sejnowski. Steps in the algorithm are (i) optimizing each individual method with respect to its correlation coefficient (Q7) for assigning a structural type from the predictive score of the method, (ii) weighting each method, (iii) combining the scores from different methods, and (iv) comparing the scores for alpha-helix, beta-strand, and coil conformational states to assign the secondary structure at each residue position. The present application to 45 globular proteins demonstrates good predictive power in cross-validation testing (with average correlation coefficients per test protein of Q7, alpha = 0.41, Q7, beta = 0.47, Q7,c = 0.41 for alpha-helix, beta-strand, and coil conformations). By the criterion of correlation coefficient (Q7) for each type of secondary structure, Q7-JASEP performs better than any of the component methods. When all protein classes are included for training and testing (by cross-validation), the results here equal the best in the literature, by the Q7 criterion. More generally, the basic algorithm can be applied to any protein class and to any type of structure/sequence or function/sequence correlation for which multiple predictive methods exist.

Algorithms↗

PubMedDate not supplied

Dynamic optimization of fed-batch bioreactors using the ant algorithm.

The ant colony algorithm, mimicking the cooperative search behavior of ants in real life, has been employed for the dynamic optimization of fed-batch bioreactors. To test the capability of this new heuristic algorithm, two well-known and extensively studied systems have been chosen. The algorithm rapidly converges to optimal feed rate profiles, which maximize the overall production of the desired product and the profits in a computationally efficient and robust manner. The optimal profiles evolved are easy to implement in plant operation. The algorithm compares favorably with the other known techniques.

Algorithms↗

PubMedDate not supplied

Graph automorphism perception algorithms in computer-enhanced structure elucidation.

The concept of graph symmetry is explained in terms of the vertex automorphism group, which is a subgroup of the complete vertex permutation group. The automorphism group can be deduced from the automorphism partition of graph vertices. An algorithm is described which constructs the automorphism group of a graph from the automorphism vertex partitioning. The algorithm is useful especially for graphs which contain more than one vertex-partition set. Several well-known topological symmetry perception algorithms that yield automorphism partitions are compared. The comparison is favorable to the Shelley-Munk algorithm, developed in the framework of the SESAMI system for computer-enhanced structure elucidation.

Algorithms↗

PubMedDate not supplied

Genetic algorithm applied to the selection of factors in principal component-artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4-dihydropyridines (nifedipine analogous).

A QSAR algorithm, principal component-genetic algorithm-artificial neural network (PC-GA-ANN), has been applied to a set of newly synthesized calcium channel blockers, which are of special interest because of their role in cardiac diseases. A data set of 124 1,4-dihydropyridines bearing different ester substituents at the C-3 and C-5 positions of the dihydropyridine ring and nitroimidazolyl, phenylimidazolyl, and methylsulfonylimidazolyl groups at the C-4 position with known Ca(2+) channel binding affinities was employed in this study. Ten different sets of descriptors (837 descriptors) were calculated for each molecule. The principal component analysis was used to compress the descriptor groups into principal components. The most significant descriptors of each set were selected and used as input for the ANN. The genetic algorithm (GA) was used for the selection of the best set of extracted principal components. A feed forward artificial neural network with a back-propagation of error algorithm was used to process the nonlinear relationship between the selected principal components and biological activity of the dihydropyridines. A comparison between PC-GA-ANN and routine PC-ANN shows that the first model yields better prediction ability.

Algorithms↗

PubMedDate not supplied

Speeding up a genetic algorithm for EPR-based spin label characterization of biosystem complexity.

Complexity of biological systems is one of the toughest problems for any experimental technique. Complex biochemical composition and a variety of biophysical interactions governing the evolution of a state of a biological system imply that the experimental response of the system would be superimposed of many different responses. To obtain a reliable characterization of such a system based on spin-label Electron Paramagnetic Resonance (EPR) spectroscopy, multiple Hybrid Evolutionary Optimization (HEO) combined with spectral simulation can be applied. Implemented as the GHOST algorithm this approach is capable of handling the huge solution space and provides an insight into the "quasicontinuous" distribution of parameters that describe the biophysical properties of an experimental system. However, the analysis procedure requires several hundreds of runs of the evolutionary optimization routine making this algorithm extremely computationally demanding. As only the best parameter sets from each run are assumed to contribute into the final solution, this algorithm appears far from being optimized. The goal of this study is to modify the optimization routine in a way that 20-40 runs would be enough to obtain qualitatively the same characterization. However, to keep the solution diversity throughout the HEO run, fitness sharing and newly developed shaking mechanisms are applied and tested on various test EPR spectra. In addition, other evolutionary optimization parameters such as population size and probability of genetic operators were also varied to tune the algorithm. According to the testing examples a speed-up factor of 5-7 was achieved.

Algorithms↗

PubMed2004

Evaluation of docking performance: comparative data on docking algorithms.

Docking molecules into their respective 3D macromolecular targets is a widely used method for lead optimization. However, the best known docking algorithms often fail to position the ligand in an orientation close to the experimental binding mode. It was reported recently that consensus scoring enhances the hit rates in a virtual screening experiment. This methodology focused on the top-ranked pose, with the underlying assumption that the orientation/conformation of the docked compound is the most accurate. In an effort to eliminate the scoring function bias, and assess the ability of the docking algorithms to provide solutions similar to the crystallographic modes, we investigated the most known docking programs and evaluated all of the resultant poses. We present the results of an extensive computational study in which five docking programs (FlexX, DOCK, GOLD, LigandFit, Glide) were investigated against 14 protein families (69 targets). Our findings show that some algorithms perform consistently better than others, and a correspondence between the nature of the active site and the best docking algorithm can be found.

Algorithms↗