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Results for “Model performance”

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PubMed1998

Integrity of the pericardium. Its beneficial effects on the protection of the right ventricle in the presence of acute pulmonary hypertension.

UNLABELLED: After cardiac transplant (CT), the right ventricle can be subject to an acute pressure overload, especially in cases where there is a pre-existing severe pulmonary hypertension. OBJECTIVES: To determine the maximum tolerance of the right ventricle (MxTRV) when faced with acute pressure overload. To study the function of both ventricles of the healthy heart (donor) when faced with different degrees of pulmonary hypertension. To detect possible interactions between the ventricles in the absence of the pericardium to approximate the experimental model to the clinical model of CT. METHODS: The pulmonary artery is progressively constrained in an experimental model until biventricular failure is detected. This experiment is performed in two different situations: with and without pericardial integrity. RESULTS: When pericardial integrity is maintained the MxTRV faced with a pressure overload is 73.2+/-8.56 mmHg. When this pressure is exceeded there is a circulatory collapse with a sharp fall in the cardiac output and in the aortic pressure. However, when pericardectomy is performed (model similar to CT), only 52+/-6.71 mmHg is tolerated (p< 0.001). CONCLUSIONS: With the pericardium open, as in CT, the maximum pressure that the right ventricle can support is significantly less than with the pericardium closed. The pericardium has a positive effect in protecting the systolic ventricular interaction.

Acute Disease↗

PubMed2005

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: hourly and seasonal ozone.

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI's assessment.

Appalachian Region↗

PubMed2001

Measuring population health risks using inpatient diagnoses and outpatient pharmacy data.

OBJECTIVE: To examine and evaluate models that use inpatient encounter data and outpatient pharmacy claims data to predict future health care expenditures. DATA SOURCES/STUDY DESIGN: The study group was the privately insured under-65 population in the 1997 and 1998 MEDSTAT Market Scan (R) Research Database. Pharmacy and disease profiles, created from pharmacy claims and inpatient encounter data, respectively, were used separately and in combination to predict each individual's subsequent-year health care expenditures. PRINCIPAL FINDINGS: The inpatient-diagnosis model predicts well for the low-hospitalization under-65 populations, explaining 8.4 percent of future individual total cost variation. The pharmacy-based and in patient-diagnosis models perform comparably overall, with pharmacy data better able to split off a group of truly low-cost people and inpatient diagnoses better able to find a small group with extremely high future costs. The model th at uses both kinds of data performed significantly better than either model alone, with an R2 value of 11.8 percent . CONCLUSIONS: Comprehensive pharmacy and inpatient diagnosis classification systems are each helpful for discriminating among people according to their expected costs. Properly organized and in combination these data are promising predictors of future costs.

Adolescent↗

PubMed1997

Manuo-ocular coordination in target tracking. I. A model simulating human performance.

During eye tracking of a self-moved target, human subjects' performance differs from eye-alone tracking of an external target. Typical latency between target and eye motion onsets is shorter, ocular smooth pursuit (SP) saturation velocity increases and the maximum target motion frequency at which the SP system functions correctly is higher. Based on a previous qualitative model, a quantitative model of the coordination control between the arm motor system and the SP system is presented and evaluated here. The model structure maintains a high level of parallelism with the physiological system. It contains three main parts: the eye motor control (containing a SP branch and a saccadic branch), the arm motor control and the coordination control. The coordination control is achieved via an exchange of information between the arm and the eye sensorimotor systems, mediated by sensory signals (vision, proprioception) and motor command copy. This cross-talk results in improved SP system performance. The model has been computer simulated and the results have been compared with human subjects' behavior observed during previous experiments. The model performance is seen to quantitatively fit data on human subjects.

Hand↗

PubMed1996

Indices for performance evaluation of predictive models in food microbiology.

Two complementary measures are proposed as simple indices of the performance of models in predictive food microbiology. The indices assess the level of confidence one can have in the predictions of the model and whether the model displays any bias which could lead to 'fail-dangerous' predictions. The use of the indices is demonstrated using data collated from independent and published literature. This analysis supports previous reports that evaluation of predictive models by comparison to published microbial growth rate data may be inappropriate because of limitations in that data. The indices may fail to reveal some forms of systematic deviation between observed and predicted behaviour. It is concluded, however, that the indices provide an objective and readily interpreted summary of model performance and may serve as a first step towards the development of an objective and useful definition of the term 'validated model' in predictive food microbiology.

Evaluation Studies as Topic↗

PubMed1996

Life-style performance: from profile to conceptual model.

The Life Style Performance Model provides a framework for knowing and understanding a person's total activity repertoire within the context of his or her human and nonhuman world. The model enables occupational therapy practitioners to gain a holistic perspective, thus ensuring that interventions will have more clearly discernible relevance to individual needs, interests, capacities, and self-other expectations. It presents a way of conceptualizing the interrelatedness of person, environment, activity profile, and quality of life. This article addresses these dynamic relationships in a manner that makes it possible to plan and implement interventions that hold maximum potential for eliciting and sustaining a person's intrinsic motivation to pursue an evolving life-style optimally satisfying to self and significant others.

Activities of Daily Living↗

PubMed1997

Differential performance of TRISS-like in early and late blunt trauma deaths.

OBJECTIVES: (1) To independently validate the Trauma and Injury Severity Score-Like (TRISS-Like) model derived by Offner et al. (Revision of TRISS for intubated patients. J Trauma. 1992;32:32-35) in a population of Canadian blunt trauma victims, and (2) to compare the ability of this model to predict mortality in early and late trauma deaths. STUDY POPULATION: Prospective cohort of blunt trauma cases with Injury Severity Score > 12 identified from the Ontario Trauma Registry over a 5-year period. STUDY DESIGN: The TRISS-Like model consisting of age, Injury Severity Score, systolic blood pressure, and best motor response of the Glasgow Coma Scale was evaluated as to its ability to predict mortality by determining the sensitivity, specificity, and the area under the receiver operating characteristic curve. The sample was then divided into early (< or = 7 days) and late mortality subgroups in which model performance was evaluated with respect to time of death. RESULTS: A total of 7,703 patients were included in this analysis. The overall mortality was 12.3%. The TRISS-Like model allowed for assessment of an additional 23% of patients than would standard TRISS and performed with a sensitivity of 97.1%, specificity of 39.8% and an area under the receiver operating characteristic curve of 0.873. Analysis of mortality with respect to time demonstrated that 75% of deaths occurred by day 7. The specificity and receiver operating characteristic area increased in the early (< or = 7 days) subgroup, 46.5% and 0.935, respectively, compared with 20.8% and 0.778 in the late mortality group. CONCLUSIONS: TRISS-Like demonstrated similar performance to that reported with the standard TRISS model but with the additional advantage that it is more generalizable because it can be applied to intubated patients. TRISS-Like demonstrated substantially superior performance in early trauma deaths compared with those that occurred late. This differential performance may be because the model does not include risk factors for late mortality.

Aged↗

PubMed2000

Cost function estimation: the choice of a model to apply to dementia.

Statistical analysis of cost data is often difficult because of highly skewed data resulting from a few patients who incur high costs relative to the majority of patients. When the objective is to predict the cost for an individual patient, the literature suggests that one should choose a regression model based on the quality of its predictions. In exploring the econometric issues, the objective of this study was to estimate a cost function in order to estimate the annual health care cost of dementia. Using different models, health care costs were regressed on the degree of dementia, sex, age, marital status and presence of any co-morbidity other than dementia. Models with a log-transformed dependent variable, where predicted health care costs were re-transformed to the unlogged original scale by multiplying the exponential of the expected response on the log-scale with the average of the exponentiated residuals, were part of the considered models. The root mean square error (RMSE), the mean absolute error (MAE) and the Theil U-statistic criteria were used to assess which model best predicted the health care cost. Large values on each criterion indicate that the model performs poorly. Based on these criteria, a two-part model was chosen. In this model, the probability of incurring any costs was estimated using a logistic regression, while the level of the costs was estimated in the second part of the model. The choice of model had a substantial impact on the predicted health care costs, e.g. for a mildly demented patient, the estimated annual health care costs varied from DKK 71 273 to DKK 90 940 (US$ 1 = DKK 7) depending on which model was chosen. For the two-part model, the estimated health care costs ranged from DKK 44714, for a very mildly demented patient, to DKK 197 840, for a severely demented patient.

Aged↗

PubMed2003

Modeling flow and sediment transport in a river system using an artificial neural network.

A river system is a network of intertwining channels and tributaries, where interacting flow and sediment transport processes are complex and floods may frequently occur. In water resources management of a complex system of rivers, it is important that instream discharges and sediments being carried by streamflow are correctly predicted. In this study, a model for predicting flow and sediment transport in a river system is developed by incorporating flow and sediment mass conservation equations into an artificial neural network (ANN), using actual river network to design the ANN architecture, and expanding hydrological applications of the ANN modeling technique to sediment yield predictions. The ANN river system model is applied to modeling daily discharges and annual sediment discharges in the Jingjiang reach of the Yangtze River and Dongting Lake, China. By the comparison of calculated and observed data, it is demonstrated that the ANN technique is a powerful tool for real-time prediction of flow and sediment transport in a complex network of rivers. A significant advantage of applying the ANN technique to model flow and sediment phenomena is the minimum data requirements for topographical and morphometric information without significant loss of model accuracy. The methodology and results presented show that it is possible to integrate fundamental physical principles into a data-driven modeling technique and to use a natural system for ANN construction. This approach may increase model performance and interpretability while at the same time making the model more understandable to the engineering community.

China↗

PubMed2006

Model based robustness analysis of an ion-exchange chromatography step.

Process development, optimization and robustness analysis for chromatographic separation are often entirely based on experimental work and generic knowledge. This paper describes a model-based approach that can be used to gain process knowledge and assist in the robustness analysis of an ion-exchange chromatography step using a model-based approach. A kinetic dispersive model, where the steric mass action model accounts for the adsorption is used to describe column performance. Model calibration is based solely on gradient elution experiments at different gradients, flow rates, pH and column loads. The position and shape of the peaks provide enough information to calibrate the model and thus single-component experiments can be avoided. The model is calibrated to the experiments and the confidence intervals for the estimated parameters are used to account for the model error throughout the analysis. The model is used to predict the result of a robustness analysis conducted as a factorial experiment and to design a robust pooling approach. The confidence intervals are used in a "worst case" approach where the parameters for the components are set at the edge of their confidence intervals to create a worst case for the removal of impurities at each point in the factorial experiment. The pooling limit was changed to ensure product quality at every point in the factorial analysis. The predicted purities and yields were compared to the experimental results to ensure that the prediction intervals cover the experimental results.

Chromatography, Ion Exchange↗

PubMed2006

Parameter identification and sedative sensitivity analysis of an agitation-sedation model.

Sedation administration and agitation management are fundamental activities in any intensive care unit. A lack of objective measures of agitation and sedation, as well as poor understanding of the underlying dynamics, contribute to inefficient outcomes and expensive healthcare. Recent models of agitation-sedation dynamics have enhanced understanding of the underlying dynamics and enable development of advanced protocols for semi-automated sedation administration. In this research, the agitation-sedation model parameters are identified using an integral-based fitting method developed in this work. Parameter variance is then analysed over 37 intensive care unit patients. The parameter identification method is shown to be effective and computationally inexpensive, making it suited to real-time clinical control applications. Sedative sensitivity, an important model parameter, is found to be both patient-specific and time-varying. However, while the variation between patients is observed to be as large as a factor 10, the observed variation in time is smaller, and varies slowly over a period of days rather than hours. The high fitted model performance across all patients show that the agitation-sedation model presented captures the fundamental dynamics of the agitation-sedation system. Overall, these results provide additional insight into the system and clinical dynamics of sedation management.

Computer Simulation↗

PubMed2006

Obstructive sleep apnea-hypopnea and neurocognitive functioning in the Sleep Heart Health Study.

BACKGROUND AND PURPOSE: Obstructive sleep apnea-hypopnea (OSAH) is associated with sleep fragmentation and nocturnal hypoxemia. In clinical samples, patients with OSAH frequently are found to have deficits in neuropsychological function. However, the nature and severity of these abnormalities in non-clinical populations is less well defined. PATIENTS AND METHODS: One hundred and forty-one participants from the Tucson, AZ and New York, NY field centers of the Sleep Heart Health Study completed a battery of neuropsychological tests for 9-40 months (mean=24 months, SD=7 months) after an unattended home polysomnogram. Sixty-seven participants had OSAH (AHI>10) and 74 did not have OSAH (control (CTL), apnea-hypopnea index (AHI)<5). In addition to the individual tests, composite variables representing attention, executive function, MotorSpeed and processing speed were constructed from the neuropsychological test battery. RESULTS: There were no significant differences in any individual neuropsychological test or composite variable between the OSAH and CTL groups. However, when time spent with O(2) saturations less than 85% was dichotomized into those participants in the top quartile of the distribution and those in the lower three quartiles, motor speed was significantly impaired in those who were more hypoxemic. In addition, poorer motor speed (model adjusted R(2)=0.242, P<0.001) and processing speed performance (model adjusted R(2)=0.122, P<0.001) were associated with more severe oxygen desaturation even after controlling for degree of daytime sleepiness, age, gender and educational level. CONCLUSIONS: Mild to moderate OSAH has little impact on the selected measures of attention, executive function, motor speed and processing speed. However, hypoxemia adversely affects both motor and processing speed. These results suggest that in middle-aged to elderly adults the neuropsychological effects of clinically unrecognized mild to moderate OSAH are neither global nor large.

Brain↗

PubMed1988

Observational learning of a left-right behavioral asymmetry in mice (Mus musculus).

B6D2F1 hybrid mice that were allowed to observe a trained female mouse open a pendulum door to the right (or to the left) to enter a food compartment later solved this problem faster than pupils that had been placed behind a visual barrier. Male pupils that had observed a "left-handed" teacher performed sinistrally; males that had observed a "right-handed" model performed dextrally. Female pupils did not exhibit their demonstrator's laterality. Observational learning may provide a means to maintain certain lateralized behaviors. Such social learning may lead to the emergence of local traditions and to the cultural diffusion of behavioral asymmetries.

Animals↗

PubMed2003

Quantitative prediction of traffic pollutant transmission into buildings.

An integrated air quality model that combines a CFD model and multi-room pollutant transport model has been developed to study the effect of traffic pollution on indoor air quality of a multi-room building located in close proximity to busy roads. The CFD model conducts the large eddy simulation of the three-dimensional turbulent flows and pollutant transport processes in outdoor, whereas the multi-room pollutant transport model performs zonal airflow and pollutant transport in indoor. The integrated model is verified with available field measurement of traffic-induced CO concentrations. Twelve scenarios of numerical experiments for various configurations of window openness are carried out to study the effects of the air change rate and the outdoor pollutant dispersion on indoor air quality. It is concluded that the windward side opening is a significant factor contributing to indoor air quality. Using air inlets on the sideward and leeward envelopes simultaneously can effectively lower the daily mean and peak indoor levels of traffic pollutants and maintain a desirable air change rate.

Air Movements↗

PubMed2002

Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method.

BACKGROUND: Skeletal muscle (SM) is an important body-composition component that remains difficult and impractical to quantify by most investigators outside of specialized research centers. A large proportion of total-body SM is found in the extremities, and a large proportion of extremity lean soft tissue is SM. A strong link should thus exist between appendicular lean soft tissue (ALST) mass and total-body SM mass. OBJECTIVE: The objective was to develop prediction models linking ALST estimated by dual-energy X-ray absorptiometry (DXA) with total-body SM quantified by multislice magnetic resonance imaging in healthy adults. DESIGN: ALST and total-body SM were evaluated with a cross-sectional design in adults [body mass index (in kg/m(2)) < 35] with an SM-prediction model developed and validated in model-development and model-validation groups, respectively. The model-development and model-validation groups included 321 and 93 ethnically diverse adults, respectively. RESULTS: ALST alone was highly correlated with total-body SM (model 1: R(2) = 0.96, SEE = 1.63 kg, P < 0.001), although multiple regression analyses showed 2 additional predictor variables: age (model 2: 2-variable combined R(2) = 0.96, SEE = 1.58 kg, P < 0.001) and sex (model 3: 3-variable combined R(2) = 0.96, SEE = 1.58 kg, P < 0.001). All 3 models performed well in the validation group. An SM-prediction model based on the SM-ALST ratio was also developed, although this model had limitations when it was applied across all subjects. CONCLUSION: Total-body SM can be accurately predicted from DXA-estimated ALST, thus affording a practical means of quantifying the large and clinically important SM compartment.

Absorptiometry, Photon↗

PubMed1994

Non-linear regression models to estimate the size of DNA fragments.

The least-squares, hyperbolic regression model is frequently used to estimate the size of unknown DNA fragments. This model avoids problems associated with semilog-plot interpolation, is computationally easy to use and provides an excellent fit to many experimental data sets. However, the methods commonly used to solve the hyperbolic regression model perform an inappropriate linearization of the original non-linear model. In this note, we describe advantages offered by standard, non-linear regression techniques, and provide computer code for a common statistical package to do these analyses.

Algorithms↗

PubMed2025

Evaluating Language Models for Biomedical Fact-Checking: A Benchmark Dataset for Cancer Variant Interpretation Verification.

Accurate interpretation of genomic variants is critical for precision oncology but remains slow and dependent on specialized expertise. Public knowledgebases such as the Clinical Interpretation of Variants in Cancer (CIViC) help by curating literature-backed variant interpretations in a structured form, yet verification and review have become major bottlenecks. To address this, we developed CIViC-Fact, a benchmark dataset and pipeline for testing automated systems that verify the accuracy of cancer variant claims. CIViC-Fact links structured claims to sentence-level supporting or refuting evidence from full-text articles, and includes expert annotations and explanations. We evaluated multiple language models. Proprietary models performed well without training, but a smaller open-source model, fine-tuned on CIViC-Fact, achieved the highest accuracy (89%). Applying our fact-checking pipeline to real CIViC entries showed that reviewing less than 20% of content, focusing on flagged entries, would be sufficient to catch over half of all errors. This AI-assisted triage greatly accelerates the review process without replacing or reducing expert insight, ensuring that existing careful oversight remains in place while curators can work more efficiently. CIViC-Fact provides a realistic, high-consequence framework for biomedical fact-checking and a path toward more rigorous and efficient knowledgebase curation.

Journal Article↗

PubMedDate not supplied

Fast and frugal models of clinical judgment in novice and expert physicians.

Our objective was to study whether "compensatory" models provide better descriptions of clinical judgment than fast and frugal models, according to expertise and experience. Fifty practitioners appraised 60 vignettes describing a child with an exacerbation of asthma and rated their propensities to admit the child. Linear logistic (LL) models of their judgments were compared with a matching heuristic (MH) model that searched available cues in order of importance for a critical value indicating an admission decision. There was a small difference between the 2 models in the proportion of patients allocated correctly (admit or not-admit decisions), 91.2% and 87.8%, respectively. The proportion allocated correctly by the LL model was lower for consultants than juniors, whereas the MH model performed equally well for both. In this vignette study, neither model provided any better description of judgments made by consultants or by pediatricians compared to other grades and specialties.

Asthma↗