PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Performance benchmarking”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 865 records · Page 48Linked to original sources
PubMed2025

Automated chromatin profiling with spa-ChIP-seq uncovers the impacts of condition variations.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to study the genomic localization of DNA-associated proteins. However, conventional protocols include multiple manual steps that can introduce inconsistency and limit scalability, thereby restricting the inclusion of appropriate replicates and controls. Although the introduction of liquid handling platforms has improved reproducibility, most existing efforts have automated only a subset of the workflow, and extending automation to efficiently map non-histone proteins, such as chromatin regulators, remains challenging. Here, we present a fully automated implementation of our previously developed single-pot ChIP-seq protocol (Texari et al. 2021), named spa-ChIP-seq, which enables scalable processing of 8 to 96 ChIP-seq samples from crosslinked cells to sequencing-ready library in approximately three days with an estimated cost of $70 per sample. Benchmarking spa-ChIP-seq against manual ChIP-seq performed in parallel demonstrates comparable signal-to-noise ratio between the two workflows. Using spa-ChIP-seq, we systematically evaluate multiple parameters including shearing and crosslinking conditions, buffer compositions, and the ratio of antibody to cell-number. We find, for the first time to our knowledge, that weaker genomic localization signals are sensitive to changing the antibody to cell-number ratio, whereas the stronger signals remain unaffected. This finding underscores the importance of maintaining consistent antibody-to-cell-number ratio for comparative studies, such as treatment responses or chromatin-QTL mapping. The spa-ChIP-seq protocol is publicly available, including deck setups, operational parameters, and scripts. We envision that this robust, cost-efficient protocol will facilitate high-throughput, reproducible ChIP-seq analyses, supporting large-scale studies of antibody validation, compound screening, population genomics, and diagnostic frameworks.

Journal Article↗
PubMed2003

Spectral biclustering of microarray data: coclustering genes and conditions.

Global analyses of RNA expression levels are useful for classifying genes and overall phenotypes. Often these classification problems are linked, and one wants to find "marker genes" that are differentially expressed in particular sets of "conditions." We have developed a method that simultaneously clusters genes and conditions, finding distinctive "checkerboard" patterns in matrices of gene expression data, if they exist. In a cancer context, these checkerboards correspond to genes that are markedly up- or downregulated in patients with particular types of tumors. Our method, spectral biclustering, is based on the observation that checkerboard structures in matrices of expression data can be found in eigenvectors corresponding to characteristic expression patterns across genes or conditions. In addition, these eigenvectors can be readily identified by commonly used linear algebra approaches, in particular the singular value decomposition (SVD), coupled with closely integrated normalization steps. We present a number of variants of the approach, depending on whether the normalization over genes and conditions is done independently or in a coupled fashion. We then apply spectral biclustering to a selection of publicly available cancer expression data sets, and examine the degree to which the approach is able to identify checkerboard structures. Furthermore, we compare the performance of our biclustering methods against a number of reasonable benchmarks (e.g., direct application of SVD or normalized cuts to raw data).

Breast Neoplasms↗
PubMed2006

Tikhonov training of the CMAC neural network.

The architecture of the cerebellar model articulation controller (CMAC) presents a rigid compromise between learning and generalization. In the presence of a sparse training dataset, this limitation manifestly causes overfitting, a drawback that is not overcome by current training algorithms. This paper proposes a novel training framework founded on the Tikhonov regularization, which relates to the minimization of the power of the sigma-order derivative. This smoothness criterion yields to an internal cell-interaction mechanism that increases the generalization beyond the degree hardcoded in the CMAC architecture while preserving the potential CMAC learning capabilities. The resulting training mechanism, which proves to be simple and computationally efficient, is deduced from a rigorous theoretical study. The performance of the new training framework is validated against comparative benchmarks from the DELVE environment.

Algorithms↗
PubMed2006

The semantic pathfinder: using an authoring metaphor for generic multimedia indexing.

This paper presents the semantic pathfinder architecture for generic indexing of multimedia archives. The semantic pathfinder extracts semantic concepts from video by exploring different paths through three consecutive analysis steps, which we derive from the observation that produced video is the result of an authoring-driven process. We exploit this authoring metaphor for machine-driven understanding. The pathfinder starts with the content analysis step. In this analysis step, we follow a data-driven approach of indexing semantics. The style analysis step is the second analysis step. Here, we tackle the indexing problem by viewing a video from the perspective of production. Finally, in the context analysis step, we view semantics in context. The virtue of the semantic pathfinder is its ability to learn the best path of analysis steps on a per-concept basis. To show the generality of this novel indexing approach, we develop detectors for a lexicon of 32 concepts and we evaluate the semantic pathfinder against the 2004 NIST TRECVID video retrieval benchmark, using a news archive of 64 hours. Top ranking performance in the semantic concept detection task indicates the merit of the semantic pathfinder for generic indexing of multimedia archives.

Abstracting and Indexing↗
PubMed1996

Health services management manpower and educational needs with American health reform.

This paper argues that our previous health services management (HSM) manpower projections may be overly optimistic as the health networks, managed care, capitated payment, and eventually global budgetary targets become the dominant themes to implement cost restraints, universal access, and social equity. HSM programs should, therefore, focus more on their educational pursuits to produce leaders for clinical management teams, who are able to allocate scarce clinical resources. A sensible strategy for HSM programs is to develop closer ties with the schools of medicine, public health, nursing, or allied health. These cooperative efforts would be particularly beneficial in teaching 'clinical-fiscal performance methodologies' to familiarize students with such concepts as clinical benchmarking, managing quality, resource management, and continuous quality improvement (CQI).

Curriculum↗
PubMed2005

Automated methods of predicting the function of biological sequences using GO and BLAST.

BACKGROUND: With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with high accuracy. Our aim is to demonstrate how accuracy benchmarking can be used in a decision-making process evaluating competing designs of biological function predictors. We utilise the Gene Ontology, GO, a directed acyclic graph of functional terms, to annotate sequences with functional information describing their biological context. Initially we examine the effect on accuracy scores of increasing the allowed distance between predicted and a test set of curator assigned terms. Next we evaluate several annotator methods using accuracy benchmarking. Given an unannotated sequence we use the Basic Local Alignment Search Tool, BLAST, to find similar sequences that have already been assigned GO terms by curators. A number of methods were developed that utilise terms associated with the best five matching sequences. These methods were compared against a benchmark method of simply using terms associated with the best BLAST-matched sequence (best BLAST approach). RESULTS: The precision and recall of estimates increases rapidly as the amount of distance permitted between a predicted term and a correct term assignment increases. Accuracy benchmarking allows a comparison of annotation methods. A covering graph approach performs poorly, except where the term assignment rate is high. A term distance concordance approach has a similar accuracy to the best BLAST approach, demonstrating lower precision but higher recall. However, a discriminant function method has higher precision and recall than the best BLAST approach and other methods shown here. CONCLUSION: Allowing term predictions to be counted correct if closely related to a correct term decreases the reliability of the accuracy score. As such we recommend using accuracy measures that require exact matching of predicted terms with curator assigned terms. Furthermore, we conclude that competing designs of BLAST-based GO term annotators can be effectively compared using an accuracy benchmarking approach. The most accurate annotation method was developed using data mining techniques. As such we recommend that designers of term annotators utilise accuracy benchmarking and data mining to ensure newly developed annotators are of high quality.

Benchmarking↗
PubMed1999

Nurses, patients benefit from evaluation process.

The privileging process at St. Marys Hospital Medical Center in Madison, WI, provides a framework for professional growth of nurses. Key areas for professional development outlined in the process include intellectual, technical, interpersonal, and ethical. Specific functions and responsibilities are delineated in charts the nurses use to track their progress.

Benchmarking↗
PubMed1998

Designing an incentive based health promotion program.

1. A health incentive program can be an effective intervention for reducing employee population risk and altering health care utilization patterns. 2. An incentive based health promotion program rewards employees for performing a selected set of behaviors. 3. Collecting supporting data (benchmarking, needs assessment, organization data, published data) provides the foundation for the health incentive program design. 4. Choose an incentive appropriate to the employee population and worksite culture.

Benchmarking↗
PubMed2026

Protein Language Model Decoys for Target Decoy Competition in Proteomics: Quality Assessment and Benchmarks.

Large-scale proteomics relies heavily on target-decoy competition for false discovery rate estimation in peptide identification, and the performance of this strategy depends strongly on the design of the decoy database. Classical generators such as reversal and shuffling remain widely used. Here, we introduce the first protein language model-based (PLM) decoy generation for peptide identification and benchmark it against classical strategies. We evaluate these approaches using three complementary quality-control layers: sequence-based separability, search-engine-agnostic spectral-space diagnostics, and end-to-end mass spectrometry benchmarks, including pipelines with rescoring. Across these analyses, PLM-based decoys are harder for sequence-only neural networks to distinguish than most classical generators, suggesting fewer obvious sequence-level artifacts. However, this signal is only weakly informative for search performance. Spectral diagnostics further show that short peptides occupy a particularly crowded target-decoy space and are therefore especially prone to local collisions across all generators. In full search pipelines, reverse decoys remain a strong baseline, and current PLM-based generators do not yet provide a clear overall advantage. We therefore view PLM-based decoys not as universal replacements for reverse decoys but as tunable tools for benchmarking, diagnostics, stress testing, and future adaptive decoy optimization, with increasing value as search models become more expressive.

Proteomics↗
PubMed1997

Multimedia benchmarking analysis for three risk assessment models: RESRAD, MMSOILS, and MEPAS.

This paper is one in a series that describes results of a benchmarking analysis initiated by the Department of Energy (DOE) and the United States Environmental Protection Agency (EPA). An overview of the study is provided in a companion paper by Laniak et al. presented in this journal issue. The three models used in the study--RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)--represent analytically-based tools that are used by the respective agencies for performing human exposure and health risk assessments. Both single media and multimedia benchmarking scenarios were developed and executed. In this paper, the multimedia scenario is examined. That scenario consists of a hypothetical landfill that initially contained uranium-238 and methylene chloride. The multimedia models predict the fate of these contaminants, plus the progeny of uranium-238, through the unsaturated zone, saturated zone, surface water, and atmosphere. Carcinogenic risks are calculated from exposure to the contaminants via multiple pathways. Results of the tests show that differences in model endpoint estimates arise from both differences in the models' mathematical formulations and assumptions related to the implementation of the scenarios.

Air Pollutants, Radioactive↗
PubMed2006

A fast and accurate online sequential learning algorithm for feedforward networks.

In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

Algorithms↗
PubMed2002

Using a pediatric database to drive quality improvement.

To survive in today's competitive market, children's hospitals must make informed decisions on cost reduction and resource optimization, while maintaining the highest quality of care. The Pediatric Health Information System (PHIS) is designed to assist children's hospitals and physicians in making these types of decisions. PHIS is a detailed comparative database that gives participating hospitals and clinicians the ability to assess and improve the resources required for patient care. PHIS data are used to compare hospital performance against clinical guidelines for the purpose of identifying opportunities that can lead to quality improvement and development of clinical benchmarks among peers. There is broad interest in the use of guidelines for clinical benchmarking because of rising health care costs, increasing demand for care, and more expensive technologies. PHIS continues to be an invaluable tool in assisting hospitals in their everyday efforts to improve efficacy and performance.

Benchmarking↗
PubMed1998

Building human resources capability in health care: a global analysis of best practice--Part II.

This paper is the second from a series of three, addressing human resource practices using best practice examples. The analysis covered is based on the experiences of organisations that have won the Malcolm Baldrige National Quality Award (MBNQA) in the USA. The subcriteria covered in this benchmarking comparative analysis covers the following areas: human resource planning and management; employee involvement; employee education and training; employee performance and recognition; employee wellbeing and satisfaction. The paper concludes by reflecting on the likely implications for health-care professionals working in the human resource field.

Awards and Prizes↗
PubMed2006

Classification of adaptive memetic algorithms: a comparative study.

Adaptation of parameters and operators represents one of the recent most important and promising areas of research in evolutionary computations; it is a form of designing self-configuring algorithms that acclimatize to suit the problem in hand. Here, our interests are on a recent breed of hybrid evolutionary algorithms typically known as adaptive memetic algorithms (MAs). One unique feature of adaptive MAs is the choice of local search methods or memes and recent studies have shown that this choice significantly affects the performances of problem searches. In this paper, we present a classification of memes adaptation in adaptive MAs on the basis of the mechanism used and the level of historical knowledge on the memes employed. Then the asymptotic convergence properties of the adaptive MAs considered are analyzed according to the classification. Subsequently, empirical studies on representatives of adaptive MAs for different type-level meme adaptations using continuous benchmark problems indicate that global-level adaptive MAs exhibit better search performances. Finally we conclude with some promising research directions in the area.

Algorithms↗
PubMed2004

CSHM: Web-based safety and health monitoring system for construction management.

INTRODUCTION: This paper describes a web-based system for monitoring and assessing construction safety and health performance, entitled the Construction Safety and Health Monitoring (CSHM) system. METHOD: The design and development of CSHM is an integration of internet and database systems, with the intent to create a total automated safety and health management tool. A list of safety and health performance parameters was devised for the management of safety and health in construction. A conceptual framework of the four key components of CSHM is presented: (a) Web-based Interface (templates); (b) Knowledge Base; (c) Output Data; and (d) Benchmark Group. RESULTS: The combined effect of these components results in a system that enables speedy performance assessment of safety and health activities on construction sites. With the CSHM's built-in functions, important management decisions can theoretically be made and corrective actions can be taken before potential hazards turn into fatal or injurious occupational accidents. IMPACT ON INDUSTRY: As such, the CSHM system will accelerate the monitoring and assessing of performance safety and health management tasks.

Benchmarking↗
PubMed1982

Development criteria for a Benchmark test program.

A Benchmark test program cannot only be used as a tool in the process of comparing the capabilities of different EDP systems, to make the decision for a new computer. Benchmark tests can serve also as a source of dynamic information on the development of performance and to predict bottlenecks with increasing workload. To gain these advantages each computer center should develop a representative model for its typical computer workload. Criteria for the development of such a Benchmark test program are described, especially for the important simulation of terminal sessions and detailed in an example.

Computers↗
PubMed1994

Knowledge gain in a problem-based surgery clerkship.

PURPOSE: To determine the magnitude of students' knowledge gain in a problem-based surgery clerkship and to identify the relationship of this gain to measures of clinical performance. METHOD: Third-year students in a problem-based surgery clerkship at the University of Kentucky College of Medicine in 1990-91 were evaluated by a comprehensive set of objective measures: surgery subject examinations of the National Board of Medical Examiners (NBME) given as pretest and posttest to assess knowledge gain, two multiple-choice quizzes, a modified-essay examination, a standardized-patient examination, and an objective structured clinical examination (OSCE). The students were also evaluated by faculty tutors and preceptors and by their peers. NBME data were available for 66 students, and data were available on the other measures for 42 students. Statistical analysis involved two-way analysis of variance, single group t-test, Pearson correlations, and partial correlations. RESULTS: The students' knowledge gain was statistically significant. The posttest mean score did not differ significantly from the national candidate mean of 500. All but two of the other knowledge and performance measures (the preceptor and tutor evaluations) correlated significantly with the knowledge gain score. The highest correlations were for peer evaluations, the standardized-patient examination, and the modified-essay examination. The overall reliability of the eight measures of student knowledge and performance was .81; deleting any measure, except the preceptor evaluation, lowered the reliability below the benchmark of .80. CONCLUSION: The results suggest that a highly significant knowledge gain occurred during the problem-based clerkship and that this gain in knowledge was closely related to improved clinical performance.

Clinical Clerkship↗