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PubMed2001

Evaluating quality indicators for patients with community-acquired pneumonia.

BACKGROUND: Several organizations have published evidence-based quality indicators for community-acquired pneumonia (CAP). However, there is variability in the types of indicators presented between organizations and the level of supporting evidence for each of the indicators. A systematic review of the literature and relevant Internet Web sites was performed to identify quality indicators for CAP that have been proposed or recommended by organizations, and each of the indicators was then critically appraised, using a well-defined set of criteria. METHODOLOGY: The MEDLINE, EMBASE, Best Evidence, and Cochrane Systematic Review databases and Internet Web sites were searched for articles and guidelines published between January 1980 and May 2001 to identify quality indicators for CAP and relevant evidence. Experts in the area of health services research were contacted to identify additional sources. A well-defined set of criteria was applied to evaluate each of the quality indicators. RESULTS: The systematic review of the literature and Internet Web sites yielded 44 CAP-specific quality indicators. The critical appraisal of these indicators yielded 16 indicators that were supported by a study that identified an association between quality of care and the process of care or outcome measure, were applied to enough patients to be able to detect clinically meaningful differences, were clinically and/or economically relevant, were measurable in a clinical practice setting, and were precise in their specifications. CONCLUSIONS: Many organizations recommend indicators for CAP. Indicators may serve as measures of clinical performance for clinicians and hospitals, may help in benchmarking, and may ultimately facilitate improvements in quality of care and cost reductions. However, CAP indicators often vary in their meaningfulness, scientific soundness, and interpretability of results. A set of five critical appraisal questions may assist in the evaluation of which quality indicators are most valid.

Community-Acquired Infections↗
PubMedDate not supplied

Recent advances in PC-Linux systems for electronic structure computations by optimized compilers and numerical libraries.

One of the most frequently used packages for electronic structure research, GAUSSIAN 98, is compiled on Linux systems with various hardware configurations, including AMD Athlon (with the "Thunderbird" core), AthlonMP, and AthlonXP (with the "Palomino" core) systems as well as the Intel Pentium 4 (with the "Willamette" core) machines. The default PGI FORTRAN compiler (pgf77) and the Intel FORTRAN compiler (ifc) are respectively employed with different architectural optimization options to compile GAUSSIAN 98 and test the performance improvement. In addition to the BLAS library included in revision A.11 of this package, the Automatically Tuned Linear Algebra Software (ATLAS) library is linked against the binary executables to improve the performance. Various Hartree-Fock, density-functional theories, and the MP2 calculations are done for benchmarking purposes. It is found that the combination of ifc with ATLAS library gives the best performance for GAUSSIAN 98 on all of these PC-Linux computers, including AMD and Intel CPUs. Even on AMD systems, the Intel FORTRAN compiler invariably produces binaries with better performance than pgf77. The enhancement provided by the ATLAS library is more significant for post-Hartree-Fock calculations. The performance on one single CPU is potentially as good as that on an Alpha 21264A workstation or an SGI supercomputer. The floating-point marks by SpecFP2000 have similar trends to the results of GAUSSIAN 98 package.

Journal Article↗
PubMed2006

Rozen's epoxidation reagent, CH3CN.HOF: a theoretical study of its structure, vibrational spectroscopy, and reaction mechanism.

Rozen's epoxidation reagent, CH(3)CN.HOF, and a prototype epoxidation reaction employing it, have been subjected to an extensive ab initio and density functional study. Its anharmonic force field reveals a very strong red shift for the OH stretch and a strong blue shift for the HOF bend, in semiquantitative agreement with experiment. The very strong hydrogen bond (8.20 kcal/mol at the W1 level) not only serves to stabilize the reactant but also considerably lowers the barrier height for epoxidation of ethylene. Moreover, the reaction byproduct HF is found to act autocatalytically. The OH moiety acquires HO(+) character in the transition state. Our W1 benchmark data for the reaction profile allow the performance of various DFT functionals to be assessed. In general, "kinetics" functionals overestimate barrier heights, the BMK functional less so than the others. The B1B95 and TPSS33B95 meta-GGA functionals both perform very well, whereas general-purpose hybrid GGAs underestimate barrier heights. The simple PBE0 functional does reasonably well.

Acetonitriles↗
PubMed2006

Microfabricated bioprocessor for integrated nanoliter-scale Sanger DNA sequencing.

An efficient, nanoliter-scale microfabricated bioprocessor integrating all three Sanger sequencing steps, thermal cycling, sample purification, and capillary electrophoresis, has been developed and evaluated. Hybrid glass-polydimethylsiloxane (PDMS) wafer-scale construction is used to combine 250-nl reactors, affinity-capture purification chambers, high-performance capillary electrophoresis channels, and pneumatic valves and pumps onto a single microfabricated device. Lab-on-a-chip-level integration enables complete Sanger sequencing from only 1 fmol of DNA template. Up to 556 continuous bases were sequenced with 99% accuracy, demonstrating read lengths required for de novo sequencing of human and other complex genomes. The performance of this miniaturized DNA sequencer provides a benchmark for predicting the ultimate cost and efficiency limits of Sanger sequencing.

Base Sequence↗
PubMed1999

Communication skills in pediatric cochlear implant recipients.

Detailed longitudinal studies of speech perception, speech production and language acquisition have justified a significant change in the demographics of congenitally and prelingually deaf children who receive cochlear implants. A trend toward earlier cochlear implantation has been justified by improvements in measures assessing these areas. To assess the influence of age at implantation on performance, age 5 years was used as a benchmark. Thirty-one children who received a Nucleus cochlear implant and use the SPEAK speech processing strategy and two children who received a Clarion cochlear implant and use the CIS strategy served as subjects. The subjects were divided into three groups based on age at implantation. The groups comprised children implanted before the age of 3 years (n = 14), children implanted between 3 years and 3 years 11 months (n = 11) and those implanted between 4 years and 5 years 3 months (n = 8). The children were further divided according to whether they used oral or total communication. The earlier-implanted groups demonstrated statistically significant improvements on measures of speech perception. Improvements in speech intelligibility as a function of age at implant were seen but did not reach statistical significance. The results of the present study demonstrate that early implantation promotes the acquisition of speaking and listening skills.

Age Factors↗
PubMedDate not supplied

Predicting neuronal responses during natural vision.

A model that fully describes the response properties of visual neurons must be able to predict their activity during natural vision. While many models have been proposed for the visual system, few have ever been tested against this criterion. To address this issue, we have developed a general framework for fitting and validating nonlinear models of visual neurons using natural visual stimuli. Our approach derives from linear spatiotemporal receptive field (STRF) analysis, which has frequently been used to study the visual system. However, prior to the linear filtering stage typical of STRFs, a linearizing transformation is applied to the stimulus to account for nonlinear response properties. We used this approach to compare two models for neurons in primary visual cortex: a nonlinear Fourier power model, which accounts for spatial phase invariant tuning, and a traditional linear model. We characterized prediction accuracy in terms of the total explainable variance, given intrinsic experimental noise. On average, Fourier power STRFs predicted 40% of explainable variance while linear STRFs were able to predict only 21% of explainable variance. The performance of the Fourier power model provides a benchmark for evaluating more sophisticated models in the future.

Animals↗
PubMed2025

EPIPDLF: a pretrained deep learning framework for predicting enhancer-promoter interactions.

MOTIVATION: Enhancers and promoters, as regulatory DNA elements, play pivotal roles in gene expression, homeostasis, and disease development across various biological processes. With advancing research, it has been uncovered that distal enhancers may engage with nearby promoters to modulate the expression of target genes. This discovery holds significant implications for deepening our comprehension of various biological mechanisms. In recent years, numerous high-throughput wet-lab techniques have been created to detect possible interactions between enhancers and promoters. However, these experimental methods are often time-intensive and costly. RESULTS: To tackle this issue, we have created an innovative deep learning approach, EPIPDLF, which utilizes advanced deep learning techniques to predict EPIs based solely on genomic sequences in an interpretable manner. Comparative evaluations across six benchmark datasets demonstrate that EPIPDLF consistently exhibits superior performance in EPI prediction. Additionally, by incorporating interpretable analysis mechanisms, our model enables the elucidation of learned features, aiding in the identification and biological analysis of important sequences. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at: https://github.com/xzc196/EPIPDLF.

Deep Learning↗
PubMed2026

FFC: a scalable FASTA compressor.

SUMMARY: FASTA is a widely used text-based format for storing nucleotide and protein sequences. The existing FASTA compressors usually focus on (slightly) improving the compression ratio, not on practical performance. We present FFC, a scalable FASTA compressor that achieves average compression speeds 4.7× and 11.4× higher than two high-performance compressors, zstd and NAF, respectively, across a benchmark set of seven single genomes. It also delivers average decompression speeds 3.5× and 2.7× higher than zstd and NAF, respectively. Although a chunk-based zstd variant with parallel decompression, pzstd, almost matches FFC speed, its compression ratio is on average by 23% worse than FFC's. For the experiment, a 14-core workstation and a RAM disk (to reduce the impact of I/O) were used. AVAILABILITY AND IMPLEMENTATION: FFC is freely available at github.com/kowallus/ffc and also as a Zenodo repository at 10.5281/zenodo.18892353, and the used datasets at 10.5281/zenodo.18873744.

Data Compression↗
PubMed2002

The Picker Patient Experience Questionnaire: development and validation using data from in-patient surveys in five countries.

OBJECTIVE: The purpose of this study was to develop and test a core set of questions to measure patients' experiences of in-patient care. Questions were selected from the bank of items developed for use in in-patient surveys undertaken by the Picker Institute for the purposes of assessing the quality of care. DESIGN: The data reported here come from surveys of patients who had attended acute care hospitals in five countries: the United Kingdom, Germany, Sweden, Switzerland, and the USA. Questionnaires were mailed to patients' homes within 1 month of discharge, either to all patients, or to a random sample, discharged during a specified period. SAMPLE: A total of 62 925 questionnaires were returned, with response rates of 65% (UK), 74% (Germany), 63% (Sweden), 52% (Switzerland), and 46% (USA). RESULTS: Fifteen items were selected from the bank of questions included in the Picker in-patient questionnaires. These items have a high degree of face validity and when summed to an index they show a high degree of construct validity and internal reliability consistency. DISCUSSION: Fifteen items derived from the longer form Picker in-patient survey have been found to provide a meaningful picture of patient experiences of health care, and constitute the 15-item Picker Patient Experience Questionnaire. These questions comprise a core set that should be measured in all in-patient facility surveys. The Picker Patient Experience Questionnaire represents a step forward in the measurement of patient experience as it provides a core set of questions around which further optional modules may be added. Scores are easy to interpret and actionable. CONCLUSION: This small set of questions could be incorporated into in-patient surveys in different settings, enabling the comparison of hospital performance and the establishment of national or international benchmarks.

Europe↗
PubMedDate not supplied

The Magnet process: one appraiser's perspective.

Achieving Magnet designation is a journey to excellence. Although excellence is never quite attained, Magnet organizations have nursing leaders who are able to implement innovative nursing programs that attract and retain nursing's best and brightest. These leaders have raised the bar on excellence and are able to demonstrate performance that is in the upper quartile among benchmarks. Even though financial pressures require astute budgetary skill, these leaders do fund research and education programs, are involved in shared leadership/governance activities, and are thus able to demonstrate fiscal accountability in the process. Nurse leaders in Magnet organizations have a highly engaged professional staff as evidenced by active participation in shared governance activities. These leaders have not only created interdisciplinary approaches to patient care and clinical documentation, acuity, and research but also they have hardwired these activities into the fabric of the organization.

Arizona↗
PubMed2005

Leadership: make it H.O.T.

A new method to motivate staff is a rigorous program called H.O.T. (Hands-On Transactional) Management.

Attitude of Health Personnel↗
PubMed2001

Hierarchical approach for computing spin glass ground states.

We describe a numerical algorithm for computing spin glass ground states with a high level of reliability. The proposed method uses a population based search and applies optimization on multiple scales. Benchmarks are given leading to estimates of the performance on large lattices.

Journal Article↗
PubMed2004

A one-layer recurrent neural network for support vector machine learning.

This paper presents a one-layer recurrent neural network for support vector machine (SVM) learning in pattern classification and regression. The SVM learning problem is first converted into an equivalent formulation, and then a one-layer recurrent neural network for SVM learning is proposed. The proposed neural network is guaranteed to obtain the optimal solution of support vector classification and regression. Compared with the existing two-layer neural network for the SVM classification, the proposed neural network has a low complexity for implementation. Moreover, the proposed neural network can converge exponentially to the optimal solution of SVM learning. The rate of the exponential convergence can be made arbitrarily high by simply turning up a scaling parameter. Simulation examples based on benchmark problems are discussed to show the good performance of the proposed neural network for SVM learning.

Journal Article↗
PubMed2004

Comparison of dose calculation algorithms in phantoms with lung equivalent heterogeneities under conditions of lateral electronic disequilibrium.

An extensive set of benchmark measurement of PDDs and beam profiles was performed in a heterogeneous layer phantom, including a lung equivalent heterogeneity, by means of several detectors and compared against the predicted dose values by different calculation algorithms in two treatment planning systems. PDDs were measured with TLDs, plane parallel and cylindrical ionization chambers and beam profiles with films. Additionally, Monte Carlo simulations by means of the PENELOPE code were performed. Four different field sizes (10 x 10, 5 x 5, 2 x 2, and 1 x 1 cm2) and two lung equivalent materials (CIRS, p(w)e=0.195 and St. Bartholomew Hospital, London, p(w)e=0.244-0.322) were studied. The performance of four correction-based algorithms and one based on convolution-superposition was analyzed. The correction-based algorithms were the Batho, the Modified Batho, and the Equivalent TAR implemented in the Cadplan (Varian) treatment planning system and the TMS Pencil Beam from the Helax-TMS (Nucletron) treatment planning system. The convolution-superposition algorithm was the Collapsed Cone implemented in the Helax-TMS. The only studied calculation methods that correlated successfully with the measured values with a 2% average inside all media were the Collapsed Cone and the Monte Carlo simulation. The biggest difference between the predicted and the delivered dose in the beam axis was found for the EqTAR algorithm inside the CIRS lung equivalent material in a 2 x 2 cm2 18 MV x-ray beam. In these conditions, average and maximum difference against the TLD measurements were 32% and 39%, respectively. In the water equivalent part of the phantom every algorithm correctly predicted the dose (within 2%) everywhere except very close to the interfaces where differences up to 24% were found for 2 x 2 cm2 18 MV photon beams. Consistent values were found between the reference detector (ionization chamber in water and TLD in lung) and Monte Carlo simulations, yielding minimal differences (0.4%+/-1.2%). The penumbra broadening effect in low density media was not predicted by any of the correction-based algorithms, and the only one that matched the experimental values and the Monte Carlo simulations within the estimated uncertainties was the Collapsed Cone Algorithm.

Algorithms↗
PubMed2000

Spontaneous speech recognition using a statistical coarticulatory model for the vocal-tract-resonance dynamics.

A statistical coarticulatory model is presented for spontaneous speech recognition, where knowledge of the dynamic, target-directed behavior in the vocal tract resonance is incorporated into the model design, training, and in likelihood computation. The principal advantage of the new model over the conventional HMM is the use of a compact, internal structure that parsimoniously represents long-span context dependence in the observable domain of speech acoustics without using additional, context-dependent model parameters. The new model is formulated mathematically as a constrained, nonstationary, and nonlinear dynamic system, for which a version of the generalized EM algorithm is developed and implemented for automatically learning the compact set of model parameters. A series of experiments for speech recognition and model synthesis using spontaneous speech data from the Switchboard corpus are reported. The promise of the new model is demonstrated by showing its consistently superior performance over a state-of-the-art benchmark HMM system under controlled experimental conditions. Experiments on model synthesis and analysis shed insight into the mechanism underlying such superiority in terms of the target-directed behavior and of the long-span context-dependence property, both inherent in the designed structure of the new dynamic model of speech.

Algorithms↗
PubMed2001

A late-stopping method for optimal aggregation of neural networks.

Ensembles of artificial neural networks have been used in the last years as classification/regression machines, showing improved generalization capabilities that outperform those of single networks. However, it has been recognized that for aggregation to be effective the individual networks must be as accurate and diverse as possible. An important problem is, then, how to tune the aggregate members in order to have an optimal compromise between these two conflicting conditions. We propose here a simple method for constructing regression/classification ensembles of neural networks that leads to overtrained aggregate members with an adequate balance between accuracy and diversity. The algorithm is favorably tested against other methods recently proposed in the literature, producing an improvement in performance on the standard statistical databases used as benchmarks. In addition, and as a concrete application, we apply our method to the sunspot time series and predict the remainder of the current cycle 23 of solar activity.

Data Collection↗
PubMed2004

High-transfer-rate high-capacity holographic disk data-storage system.

We describe the design and implementation of a high-data-rate high-capacity digital holographic storage disk system. Various system design trade-offs that affect density and data-rate performance are described and analyzed. In the demonstration system that we describe, high-density holographic recording is achieved by use of high-resolution short-focal-length optics and correlation shift multiplexing in photopolymer disk media. Holographic channel decoding at a 1-Gbit/s data rate is performed by custom-built electronic hardware. A benchmark sustained optical data-transfer rate of 10 Gbits/s has been successfully demonstrated.

Journal Article↗