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At least 1,171 records · Page 65Linked to original sources
PubMed1990

A comparison of the parameter estimating procedures for the Michaelis-Menten model.

The performance of four parameter estimating procedures for the estimation of the adjustable parameters in the Michaelis-Menten model, the maximum initial rate Vmax, and the Michaelis-Menten constant Km, including Lineweaver & Burk transformation (L-B), Eadie & Hofstee transformation (E-H), Eisenthal & Cornish-Bowden transformation (ECB), and Hsu & Tseng random search (H-T) is compared. The analysis of the simulated data reveals the followings: (i) Vmax can be estimated more precisely than Km. (ii) The sum of square errors, from the smallest to the largest, follows the sequence H-T, E-H, ECB, L-B. (iii) Considering the sum of square errors, relative error, and computing time, the overall performance follows the sequence H-T, L-B, E-H, ECB, from the best to the worst. (iv) The performance of E-H and ECB are on the same level. (v) L-B and E-H are appropriate for pricesly measured data. H-T should be adopted for data whose error level are high. (vi) Increasing the number of data points has a positive effect on the performance of H-T, and a negative effect on the performance of L-B, E-H, and ECB.

Animals↗
PubMed2003

Integrated healthcare networks' performance: a growth curve modeling approach.

This study examines the effects of integration on the performance ratings of the top 100 integrated healthcare networks (IHNs) in the United States. A strategic-contingency theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. To create a database for the panel study, the top 100 IHNs selected by the SMG Marketing Group in 1998 were followed up in 1999 and 2000. The data were merged with the Dorenfest data on information system integration. A growth curve model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' performance in 1998 and their subsequent rankings in the consecutive years were analyzed. IHNs' initial performance scores were positively influenced by network size, number of affiliated physicians and profit margin, and were negatively associated with average length of stay and technical efficiency. The continuing high performance, judged by maintaining higher performance scores, tended to be enhanced by the use of more managerial or executive decision-support systems. Future studies should include time-varying operational indicators to serve as predictors of network performance.

Case Management↗
PubMed2004

Research requirements for operational decision-making using models of fatigue and performance.

Sustained human performance is critical to job and mission success in many federal agencies including national defense, aerospace exploration, and transportation. For the responsible agencies, applications of the basic biomedical and applied human factors science provide the best available solutions to help individuals perform more effectively and with increased safety. Key products of this research are biomathematical models that predict periods of impaired performance, with applications in planning tools, real time monitoring, and intervention decision aids. Since it is difficult to quantify the number of judgment errors or accidents averted, metrics of success for fatigue management systems must be largely based on the accuracy of performance predictions derived from laboratory-based research studies and the extent to which such results can be generalized to the field environment. Performance metrics must, at a minimum, be correlated with occupational task performance to demonstrate relevance to real-world applications. This paper outlines broad goals for human effectiveness research related to fatigue, alertness, and performance. To advance from the present state of knowledge to useful predictive models requires a well-coordinated commitment from federal agencies. Users should be made aware that current models and tests are not likely to encompass all of the aspects of human performance that are relevant to field environments and occupations.

Decision Support Techniques↗
PubMed1997

Top-down learning of low-level vision tasks.

Perceptual tasks such as edge detection, image segmentation, lightness computation and estimation of three-dimensional structure are considered to be low-level or mid-level vision problems and are traditionally approached in a bottom-up, generic and hard-wired way. An alternative to this would be to take a top-down, object-class-specific and example-based approach. In this paper, we present a simple computational model implementing the latter approach. The results generated by our model when tested on edge-detection and view-prediction tasks for three-dimensional objects are consistent with human perceptual expectations. The model's performance is highly tolerant to the problems of sensor noise and incomplete input image information. Results obtained with conventional bottom-up strategies show much less immunity to these problems. We interpret the encouraging performance of our computational model as evidence in support of the hypothesis that the human visual system may learn to perform supposedly low-level perceptual tasks in a top-down fashion.

Algorithms↗
PubMed2000

Simulation of cow-calf production systems in a range environment: II. Model evaluation.

Development of a general beef cattle simulation model was described in a companion paper. The objectives of this research were to demonstrate and evaluate the model's performance. Four experiments were conducted to demonstrate 1) life-cycle weight and body condition changes for different genotypes raised in a northern range environment; 2) responses in forage intake and weight to changes in forage quality, protein supplementation, and cow physiological state; 3) responses in reproduction, weight, body condition, and calf growth to differences in pre- and postpartum nutrition; and 4) differences in enterprise efficiency and profit for different genotypes and mating systems. Results indicated that the model performs acceptably for the types of situations for which it was designed and highlighted areas of animal science where more information is needed in order to better understand and manipulate beef cattle systems. Computer simulation models are useful tools to facilitate the integration of scientific concepts and to help scientists, teachers, and producers better understand the complex production systems that they study and manage. In addition to addressing enterprise-level problems that are beyond the scope of traditional experimentation, modeling and simulation help identify research needs and foster exchange among disciplines.

Animal Feed↗
PubMed1987

Self-expanding metallic stents: preliminary evaluation in an atherosclerotic model.

The performance of the self-expanding stainless steel (Gianturco) stent in atherosclerotic arteries was examined in a rabbit model. Atherosclerosis was induced by supplementing rabbit chow with 6% peanut oil and 2% cholesterol followed by endothelial disruption of the abdominal aorta with a balloon catheter and continuation on the atherogenic diet for the remainder of the study. Eighteen stents, 1 cm in length and 4 or 5 mm in diameter when fully expanded, were placed in atherosclerotic stenotic lesions in six rabbits. Luminal distention was consistently achieved. At 8 weeks follow-up, no luminal narrowing, stent migration, thrombus formation or branch vessel occlusion had occurred. Atherosclerotic neointimal proliferation occurred around the stent wires following placement, but did not cause significant luminal narrowing.

Animals↗
PubMed2005

An episodic process model of affective influences on performance.

In this article, the authors present a model linking immediate affective experiences to within-person performance. First, the authors define a time structure for performance (the performance episode) that is commensurate with the dynamic nature of affect. Next, the authors examine the core cognitive and regulatory processes that determine performance for 1 person during any particular episode. Third, the authors describe how various emotions and moods influence the intermediary performance processes, thereby affecting performance. In the final section of the article, the authors discuss limitations, future research directions, and practical implications for their episodic process model of affect and performance.

Adaptation, Psychological↗
PubMed1987

A fuzzy model of the helmsman performing a course-keeping task.

The development of a model that describes the control characteristics of a helmsman whilst course-keeping is reported herein. The basic element of the helmsman model is a fuzzy role-based course-keeping algorithm. The model is used in digital computer simulations to control the non-linear yaw dynamics of a Royal Navy warship model which is subjected to sea state disturbances. For comparison purposes, another helmsman model is developed using linear systems theory. Validation of both models is made by comparing real-time analogue simulation results produced by actual helmsmen with those obtained digitally. Both helmsman models are found to reproduce acceptable yaw response predictions, whilst the fuzzy model more closely approximates the control input of a helmsman.

Journal Article↗
PubMed1996

Development, application, and limitation of a stochastic Markov model in explaining championship squash performance.

This study reports a stochastic (Markov) model for squash which uses empirical data to transit event states on a shot by shot basis. This offers more information than traditional models with regard to how points were won or lost and the potential for predicting future athletic performance from a priori observation. The predictive capacity of the model, however, is presently restricted because the observed behaviors (shots) and associated outcomes (winners, errors and lets) are statistically variant (p < .25). A player does not produce a consistent athletic response to the same preceding condition when competing against different opponents, although it is unclear at present whether this observation is a function of the particular analysis employed. Nevertheless, the modeling of athletic behavior is a way to search for critical data which underpin competitive sport performance.

Competitive Behavior↗
PubMed1991

Modeling the cost and performance of early identification protocols.

This is the first in a series of three papers concerned with the early identification of hearing loss. In this paper, a simple model is presented that permits the calculation of the performance and cost of early identification protocols. In the second paper (Turner, in press), this model is used to compare four early identification protocols that differ in hearing screening strategies. The third paper (Turner, in press) examines the factors that influence the early identification protocol. The model described in this paper is sufficiently general to accommodate most early identification strategies including those that meet the goal of identification and habilitation by 6 months. The model measures protocol performance using hit rate, false alarm rate, and selected posterior probabilities. The model also calculates two measures of the financial cost. One measure reflects the cost of implementing the protocol; the other reflects the cost-effectiveness of the protocol. The parameters required by the model are also specified and are based on published clinical data. The model is provided to help audiologists design and select early identification protocols that are optimum for their particular clinical situation.

Clinical Protocols↗
PubMed2005

Architectures for high-performance FPGA implementations of neural models.

As the complexity of neural models continues to increase (larger populations, varied ionic conductances, more detailed morphologies, etc) traditional software-based models have difficulty scaling to reach the performance levels desired. This paper describes the use of FPGAs, or field programmable gate arrays, to easily implement a wide variety of neural models with the performance of custom analogue circuits or computer clusters, the reconfigurability of software, and at a cost rivalling personal computers. FPGAs reach this level of performance by enabling the design of neural models as parallel processed data paths. These architectures provide for a wide range of single-compartment, multi-compartment and population models to be readily converted to FPGA implementations. Generalized architectures are described for the efficient modelling of a first-order, nonlinear differential equation in throughput maximizing or latency minimizing data-path configurations. The homogeneity of population and multicompartment models is exploited to form deep pipelines for improved performance. Limitations of FPGA architectures and future research areas are explored.

Animals↗
PubMed2006

[Does a higher coronary artery bypass graft surgery volume always have a low in-hospital mortality rate in Korea?].

OBJECTIVES: To propose a risk-adjustment model with using insurance claims data and to analyze whether or not the outcomes of non-emergent and isolated coronary artery bypass graft surgery (CABG) differed between the low- and high-volume hospitals for the patients who are at different levels of surgical risk. METHODS: This is a cross-sectional study that used the 2002 data of the national health insurance claims. The study data set included the patient level data as well as all the ICD-10 diagnosis and procedure codes that were recorded in the claims. The patient's biological, admission and comorbidity information were used in the risk-adjustment model. The risk factors were adjusted with the logistic regression model. The subjects were classified into five groups based on the predicted surgical risk: minimal (<0.5%), low (0.5% to 2%), moderate (2% to 5%), high (5% to 20%), and severe (=20%). The differences between the low- and high-volume hospitals were assessed in each of the five risk groups. RESULTS: The final risk-adjustment model consisted of ten risk factors and these factors were found to have statistically significant effects on patient mortality. The C-statistic (0.83) and Hosmer-Lemeshow test (x2=6.92, p=0.55) showed that the model's performance was good. A total of 30 low-volume hospitals (971 patients) and 4 high-volume hospitals (1,087 patients) were identified. Significant differences for the in-hospital mortality were found between the low- and high-volume hospitals for the high (21.6% vs. 7.2%, p=0.00) and severe (44.4% vs. 11.8%, p=0.00) risk patient groups. CONCLUSIONS: Good model performance showed that insurance claims data can be used for comparing hospital mortality after adjusting for the patients' risk. Negative correlation was existed between surgery volume and in-hospital mortality. However, only patients in high and severe risk groups had such a relationship.

Aged↗
PubMed2025

Robustness of Ancestral Sequence Reconstruction to Among-site and Among-lineage Evolutionary Heterogeneity.

Ancestral sequence reconstruction is typically performed using homogeneous evolutionary models, which assume that the same substitution propensities affect all sites and lineages. These assumptions are routinely violated: heterogeneous structural and functional constraints favor different amino acids at different sites, and these constraints often change among lineages as epistatic substitutions accrue at other sites. To evaluate how violations of the homogeneity assumption affect ancestral sequence reconstruction under realistic conditions, we developed site-specific substitution models and parameterized them using data from deep mutational scanning experiments on three protein families; we then used these models to perform ancestral sequence reconstruction on the empirical alignments and on alignments simulated under heterogeneous conditions derived from the experiments. Extensive among-site and -lineage heterogeneity is present in these datasets, but the sequences reconstructed from empirical alignments are almost identical when heterogeneous or homogeneous models are used for ancestral sequence reconstruction. Using models fit to deep mutational scanning data from distantly related proteins in which mutational effects are very different also has a minimal impact on ancestral sequence reconstruction. The rare differences occur primarily where phylogenetic signal is weak-at fast-evolving sites and nodes connected by long branches. When ancestral sequence reconstruction is performed on simulated data, errors in the reconstructed sequences become more likely as branch lengths increase, but incorporating heterogeneity into the model does not improve accuracy. These data establish that ancestral sequence reconstruction is robust to unincorporated realistic forms of evolutionary heterogeneity, because the primary determinant of ancestral sequence reconstruction is phylogenetic signal, not the substitution model. The best way to improve accuracy is therefore not to develop more elaborate models but to apply ancestral sequence reconstruction to densely sampled alignments that maximize phylogenetic signal at the nodes of interest.

Phylogeny↗
PubMed1975

Drug interactions: the effects of alcohol and meprobamate applied singly and jointly in human subjects. III. The concentrations of alcohol and meprobamate in the blood and their effects on performance; application of mathematical models.

The relations between the levels of alcohol and meprobamate in the blood and performance on a visual-motor coordination tracking task were analyzed by a general system of mathematical models, using data from Experiment V by Carpenter et al. [J. Stud. Alc., Suppl. No. 7, pp. 54-139, 1975]. The derivation of the models is described. In general, the relationship between blood alcohol concentration (BAC) and performance was nonmonotonic: best performance occurred at BACS of 10 to 20 mg per 100 ml. The relationship between meprobamate concentration (BMC) and performance was monotonic: performance deteriorated with increasing BMC. The results of the reaction latency measure, howevr, showed no consistent relationship with BAC or BMC. The action of alcohol can be represented by a model which involves 2 distinct sites of action; that of meprobamate, 1 site. It could not be determined whether the site of action of meprobamate is distinct from those of alcohol because the blood levels of the drugs were not high enough. The implications of the results are discussed, with particular reference to the quantitative description of the joint action of drugs and the design of future experiments.

Drug Combinations↗
PubMed2000

Fourier analysis of sinusoidally driven thalamocortical relay neurons and a minimal integrate-and-fire-or-burst model.

We performed intracellular recordings of relay neurons from the lateral geniculate nucleus of a cat thalamic slice preparation. We measured responses during both tonic and burst firing modes to sinusoidal current injection and performed Fourier analysis on these responses. For comparison, we constructed a minimal "integrate-and-fire-or-burst" (IFB) neuron model that reproduces salient features of the relay cell responses. The IFB model is constrained to quantitatively fit our Fourier analysis of experimental relay neuron responses, including: the temporal tuning of the response in both tonic and burst modes, including a finding of low-pass and sometimes broadband behavior of tonic firing and band-pass characteristics during bursting, and the generally greater linearity of tonic compared with burst responses at low frequencies. In tonic mode, both experimental and theoretical responses display a frequency-dependent transition from massively superharmonic spiking to phase-locked superharmonic spiking near 3 Hz, followed by phase-locked subharmonic spiking at higher frequencies. Subharmonic and superharmonic burst responses also were observed experimentally. Characterizing the response properties of the "tuned" IFB model leads to insights regarding the observed stimulus dependence of burst versus tonic response mode in relay neurons. Furthermore the simplicity of the IFB model makes it a candidate for large scale network simulations of thalamic functioning.

Animals↗
PubMed1992

Isoresponse time regions for the evaluation of visual search performance in ergonomic interface models.

Computer-aided ergonomic evaluation models often provide a limited function of visual performance, usually in the form of visibility tests at any given location. It is, however, of great importance to complete a visual task in a predetermined time successfully or to predict the time to complete the task, e.g., a task of high-level control such as aircraft flight operations. In this study, isoresponse time regions which have an effect on visual performance in real-life situations are presented as an effort to complement aforementioned shortcomings of ergonomic interface models. A multiple regression was used to provide equal response time regions, being asymmetrical in shape. In addition, the fuzzy linear regression (FLR) model was introduced to provide a fuzzy set from which a decision-maker might select appropriately. It provided similar fitted values with having the advantage of utilizing the interval of those fitted values over the conventional regression model. The results can be applied effectively to the design of an interface for diverse visual tasks in real situations.

Adult↗
PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95&#xa0;% CI 0.85-0.94; 95&#xa0;% prediction interval 0.62-0.98), with sensitivity of 0.80 (95&#xa0;% CI 0.77-0.83) and specificity of 0.87 (95&#xa0;% CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗