scholarly journals Non-Spatial Impairments Affect False-Positive Neglect Diagnosis Based on Cancellation Tasks

2020 ◽  
Vol 26 (7) ◽  
pp. 668-678 ◽  
Author(s):  
Hanne Huygelier ◽  
Margaret Jane Moore ◽  
Nele Demeyere ◽  
Céline R. Gillebert
Keyword(s):  
Test Performance ◽  
False Positive ◽  
Standard Procedure ◽  
Model Performance ◽  
False Positives ◽  
Spatial Bias ◽  
Multiple Tests ◽  
Left And Right ◽  
The Difference ◽  
The Impact

AbstractObjective:To diagnose egocentric neglect after stroke, the spatial bias of performance on cancellation tasks is typically compared to a single cutoff. This standard procedure relies on the assumption that the measurement error of cancellation performance does not depend on non-spatial impairments affecting the total number of cancelled targets. Here we assessed the impact of this assumption on false-positive diagnoses.Method:We estimated false positives by simulating cancellation data using a binomial model. Performance was summarised by the difference in left and right cancelled targets (R-L) and the Centre of Cancellation (CoC). Diagnosis was based on a fixed cutoff versus cutoffs adjusted for the total number of cancelled targets and on single test performance versus unanimous or proportional agreement across multiple tests. Finally, we compared the simulation findings to empirical cancellation data acquired from 651 stroke patients.Results:Using a fixed cutoff, the rate of false positives depended on the total number of cancelled targets and ranged from 10% to 30% for R-L scores and from 10% to 90% for CoC scores. The rate of false positives increased even further when diagnosis was based on proportional agreement across multiple tests. Adjusted cutoffs and unanimous agreement across multiple tests were effective at controlling false positives. For empirical data, fixed versus adjusted cutoffs differ in estimation of neglect prevalence by 13%, and this difference was largest for patients with non-spatial impairments.Conclusions:Our findings demonstrate the importance of considering non-spatial impairments when diagnosing neglect based on cancellation performance.

scholarly journals The Impact of Increasing Prevalence, False Omissions, and Diagnostic Uncertainty on Coronavirus Disease 2019 (COVID-19) Test Performance

2021 ◽  
Author(s):  
Gerald J. Kost
Keyword(s):  
Test Performance ◽  
Influenza A ◽  
Geometric Mean ◽  
False Positives ◽  
Test Quality ◽  
False Negatives ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Tier 3 ◽  
The Impact

ABSTRACT Context. Coronavirus disease 2019 (COVID-19) test performance depends on predictive values in settings of increasing disease prevalence. Geospatially distributed diagnostics with minimal uncertainty facilitate efficient point-of-need strategies. Objectives. To use original mathematics to interpret COVID-19 test metrics; assess Food and Drug Administration Emergency Use Authorizations and Health Canada targets; compare predictive values for multiplex, antigen, polymerase chain reaction kit, point-of-care antibody, and home tests; enhance test performance; and improve decision-making. Design. PubMed/newsprint generated articles documenting prevalence. Mathematica and open access software helped perform recursive calculations, graph multivariate relationships, and visualize performance by comparing predictive value geometric mean-squared patterns. Results. Tiered sensitivity/specificity comprise: T1) 90%, 95%; T2) 95%, 97.5%; and T3) 100%, ≥99%. Tier 1 false negatives exceed true negatives at >90.5% prevalence; false positives exceeded true positives at <5.3% prevalence. High sensitivity/specificity tests reduce false negatives and false positives yielding superior predictive values. Recursive testing improves predictive values. Visual logistics facilitate test comparisons. Antigen test quality falls off as prevalence increases. Multiplex severe acute respiratory syndrome (SARS)-CoV-2)*Influenza A/B*Respiratory-Syncytial Virus (RSV) testing performs reasonably well compared to Tier 3. Tier 3 performance with a Tier 2 confidence band lower limit will generate excellent performance and reliability. Conclusions. The overriding principle is select the best combined performance and reliability pattern for the prevalence bracket. Some public health professionals recommend repetitive testing to compensate for low sensitivity. More logically, improved COVID-19 assays with less uncertainty conserve resources. Multiplex differentiation of COVID-19 from Influenza A/B-RSV represents an effective strategy if seasonal flu surges next year.

scholarly journals Prevalence and Risk Factors of Discordance between Left- and Right-Hip Bone Mineral Density Using DXA

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Aziza Mounach ◽  
Asmaa Rezqi ◽  
Imad Ghozlani ◽  
Lahsen Achemlal ◽  
Ahmed Bezza ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Mineral Density ◽  
Detectable Difference ◽  
Smallest Detectable Difference ◽  
Left And Right ◽  
The Difference ◽  
Highly Correlated ◽  
The Impact ◽  
Confounding Parameters

To determine the prevalence of significant left-right differences in hip bone mineral density (BMD), and the impact of this difference on osteoporosis diagnosis, we measured bilateral proximal femora using dual energy X-ray absorptiometry (DXA) in 3481 subjects (608 males, 2873 females). The difference between left and right hip was considered significant if it exceeded the smallest detectable difference (SDD) for any of the three hip subregions. Contralateral femoral BMD was highly correlated at all measuring sites (–0.95). However, significant left-right differences in BMD were common: the difference exceeded the SDD for 54% of patients at total hip, 52.1% at femoral neck, and 57.7% at trochanter. The prevalence of left-right differences was greater in participants >65 years. For 1169 participants with normal spines, 22 (1.9%) had discordant left-right hips in which one hip was osteoporotic; for 1349 patients with osteopenic spines, 94 (7%) had osteoporosis in one hip. Participants with BMI < 20 kg/m2 were more likely to show major T-score discordance (osteoporosis in one hip and normal BMD in the other). Multiple regression analysis showed that the only significant statically parameter that persists after adjusting for all potential confounding parameters were age over 65 years.

scholarly journals A two-layer canopy with thermal inertia for an improved modelling of the sub-canopy snowpack energy-balance

2015 ◽  
Vol 8 (1) ◽  
pp. 209-262 ◽  
Author(s):  
I. Gouttevin ◽  
M. Lehning ◽  
T. Jonas ◽  
D. Gustafsson ◽  
M. Mölder
Keyword(s):  
Energy Balance ◽  
Temperature Drop ◽  
Model Performance ◽  
Thermal Inertia ◽  
Thermal Response ◽  
Canopy Temperature ◽  
Night Time ◽  
The Difference ◽  
Snow Model ◽  
The Impact

Abstract. A new, two-layer canopy module with thermal inertia as part of the detailed snow model SNOWPACK (version 3.2.1) is presented and evaluated. This module is designed to reproduce the difference in thermal response between leafy and woody canopy elements, and their impact on the underlying snowpack energy balance. Given the number of processes resolved, the SNOWPACK model with its enhanced canopy module constitutes a very advanced, physics-based atmosphere-to-soil-through-canopy-and-snow modelling chain. Comparisons of modelled sub-canopy thermal radiation to stand-scale observations at an Alpine site (Alptal, Switzerland) demonstrate the improvements of the new canopy module. Both thermal heat mass and the two-layer canopy formulation contribute to reduce the daily amplitude of the modelled canopy temperature signal, in agreement with observations. Particularly striking is the attenuation of the night-time drop in canopy temperature, which was a key model bias. We specifically show that a single-layered canopy model is unable to produce this limited temperature drop correctly. The impact of the new parameterizations on the modelled dynamics of the sub-canopy snowpack is analysed and yields consistent results but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performance against snow data. The new model is also successfully tested without specific tuning against measured tree temperatures and biomass heat storage fluxes at the boreal site of Norunda (Sweden). This provides an independent assessment of its physical consistency and stresses the robustness and transferability of the parameterizations used.

scholarly journals Incorporating Robustness to Imaging Physics into Radiomic Feature Selection for Breast Cancer Risk Estimation

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5497
Author(s):  
Raymond J. Acciavatti ◽  
Eric A. Cohen ◽  
Omid Haji Maghsoudi ◽  
Aimilia Gastounioti ◽  
Lauren Pantalone ◽  
...  
Keyword(s):  
Risk Estimation ◽  
Characteristic Curve ◽  
Model Performance ◽  
Image Sharpness ◽  
Data Set ◽  
Cancer Occurrence ◽  
Measure Model ◽  
Left And Right ◽  
The Difference ◽  
One Year

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns—a woman’s left and right breasts. From 341 features, we identified “robust” features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross‑validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles.

Results of pig progeny testing in Great Britain

1965 ◽  
Vol 7 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Charles Smith
Keyword(s):  
Great Britain ◽  
Test Performance ◽  
Genetic Correlations ◽  
Performance Testing ◽  
Progeny Testing ◽  
Test Results ◽  
Genetic Changes ◽  
Mild Degree ◽  
The Difference ◽  
The Impact

SUMMARYFrom 1958 to 1962 over 800 boars and 3,000 sows were progeny tested at the national pig progeny testing stations in Great Britain. Their test results for four traits (daily gain, feed efficiency, average backfat and carcass length) have been used to study the amount and effectiveness of selection and to review the use of the test facilities and their effect on pig improvement.The amount of selection on test results was studied by measuring the difference in performance of animals with sons subsequently tested and all contemporary tested animals. The selection differentials found were from 0·05 to 0·30 standard deviation units for the four traits studied which represents a rather mild degree of selection. Thus selection could have had only a small effect in improving the testing population. In fact sons of tested animals showed little advantage over their contemporaries in test performance. Parent-offspring regressions were calculated and these, in agreement with theoretical estimates, indicated that selection would be effective and would lead to genetic changes in any of the four traits studied. Genetic correlations among the four traits were also calculated and indicated genetic compatability in improving the four traits concurrently.Two proposals intended to increase the impact of testing on pig improvement are put forward. These are (1) to restrict the testing facilities to a small nucleus set of breeders who could concentrate on testing and selection and (2) to replace the progeny testing by performance testing which would allow a more intense selection and a greater rate of improvement for the same testing facilities.

Assessing the Impact of Internet Testing

2011 ◽  
pp. 177-189 ◽  
Author(s):  
Wm. Benjamin Martz Jr. ◽  
Morgan M. Shepherd
Keyword(s):  
Social Environment ◽  
Test Performance ◽  
Testing Procedure ◽  
The Other ◽  
Future Research ◽  
Course Content ◽  
The Social ◽  
The Difference ◽  
Time Of Year ◽  
The Impact

This chapter provides the results of a comparison between two sections of a graduate programming class, where one was an on-campus class and the other, a distance class. The course content, instructor, syllabus, lecture materials, notes, assessments and semester (time of year) were the same. Both groups were surveyed to test their satisfaction with the testing procedure and with their perception of certain aspects of the social environment. The results showed differences in perceived test performance. Two conjectures about possible causes underlying the difference and suggestions for possible future research end the discussion.

scholarly journals Evaluating the impact of spatial variability of precipitation on streamflow simulation using a SWAT model

Water Policy ◽  
2018 ◽  
Vol 21 (1) ◽  
pp. 178-196 ◽  
Author(s):  
Feng Xue ◽  
Peng Shi ◽  
Simin Qu ◽  
Jianjin Wang ◽  
Yanming Zhou
Keyword(s):  
Spatial Variability ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Coefficient Of Determination ◽  
Interpolation Methods ◽  
Monthly Streamflow ◽  
Areal Precipitation ◽  
The Difference ◽  
The Impact

Abstract The spatial variability of precipitation is often considered to be a major source of uncertainty for hydrological models. The widely used Soil and Water Assessment Tool (SWAT) is insufficient to calculate a sub-basin's mean areal precipitation (MAP) since it only uses data from the rainfall station nearest to the centroid of each sub-basin. Therefore, Inverse Distance Weighting (IDW), Thiessen Polygons (TP) and Ordinary Kriging (OK) were applied as alternative interpolation methods in this study to calculate sub-basin MAP. The MAP results from the four methods used for the Xixian Basin were quite different in terms of amount and spatial distribution. The SWAT model performance was then assessed at monthly and daily timescales, based on Nash–Sutcliffe efficiency (NSE), the Coefficient of Determination (R2) as well as Percentage Bias (PBIAS) at the basin outlet. The results under different network densities and spatial distributions of gauge stations indicated that the modified MAP models did not have an advantage over the default Nearest Neighbour (NN) method in simulating monthly streamflow. However, the modified areal precipitation obtained through IDW and TP showed relatively high accuracy in simulating daily flows as the applied rainfall stations changed. The difference in terms of estimated rainfall and streamflow in this study confirmed that evaluation of interpolation methods is necessary before building a SWAT model.

scholarly journals Investigation of ITD Symmetry in Measured HRIRs

2016 ◽  
Author(s):  
Andrea F. Genovese ◽  
Jordan Juras ◽  
Chris Miller ◽  
Agnieszka Roginska
Keyword(s):  
Interaural Time Difference ◽  
Measurement Techniques ◽  
Just Noticeable Difference ◽  
Non Invasive ◽  
3D Sound ◽  
Left And Right ◽  
The Difference ◽  
Public Datasets ◽  
Invasive Techniques ◽  
The Impact

The Interaural Time Difference is one of the primary localiza- tion cues for 3D sound. However, due to differences in head and ear anthropometry across the population, ITDs related to a sound source at a given location around the head will differ from sub- ject to subject. Furthermore, most individuals do not possess sym- metrical traits between the left and right pinnae. This fact may cause an angle-dependent ITD asymmetry between locations mir- rored across the left and right hemispheres. This paper describes an exploratory analysis performed on publicly available databases of individually measured HRIRs. The analysis was first performed separately for each dataset in order to explore the impact of dif- ferent formats and measurement techniques, and then on pooled sets of repositories, in order to obtain statistical information closer to the population values. Asymmetry in ITDs was found to be consistently more prominent in the rear-lateral angles (approxi- mately between 90° and 130° azimuth) across all databases inves- tigated, suggesting the presence of a sensitive region. A signifi- cant difference between the peak asymmetry values and the aver- age asymmetry across all angles was found on three out of four examined datasets. These results were further explored by pooling the datasets together, which revealed an asymmetry peak at 110° that also showed significance. Moreover, it was found that within the region of sensitivity the difference between specular ITDs ex- ceeds the just noticeable difference values for perceptual discrim- ination at all frequency bands. These findings validate the sta- tistical presence of ITD asymmetry in public datasets of individ- ual HRIRs and identify a significant, perceptually-relevant, region of increased asymmetry. Details of these results are of interest for HRIR modeling and personalization techniques, which should consider implementing compensation for asymmetric ITDs when aiming for perceptually accurate binaural displays. This work is part of a larger study aimed at binaural-audio personalization and user-characterization through non-invasive techniques.

scholarly journals Uncertainty in the Number of Calibration Repetitions of a Hydrologic Model in Varying Climatic Conditions

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2362
Author(s):  
Patrik Sleziak ◽  
Ladislav Holko ◽  
Michal Danko ◽  
Juraj Parajka
Keyword(s):  
Differential Evolution Algorithm ◽  
Model Performance ◽  
Hydrologic Model ◽  
Climatic Conditions ◽  
Data Set ◽  
Climate Conditions ◽  
Daily Data ◽  
Model Efficiency ◽  
The Difference ◽  
The Impact

The objective of this study is to examine the impact of the number of calibration repetitions on hydrologic model performance and parameter uncertainty in varying climatic conditions. The study is performed in a pristine alpine catchment in the Western Tatra Mountains (the Jalovecký Creek catchment, Slovakia) using daily data from the period 1989–2018. The entire data set has been divided into five 6-years long periods; the division was based on the wavelet analysis of precipitation, air temperature and runoff data. A lumped conceptual hydrologic model TUW (“Technische Universität Wien”) was calibrated by an automatic optimisation using the differential evolution algorithm approach. To test the effect of the number of calibrations in the optimisation procedure, we have conducted 10, 50, 100, 300, 500 repetitions of calibrations in each period and validated them against selected runoff and snow-related model efficiency criteria. The results showed that while the medians of different groups of calibration repetitions were similar, the ranges (max–min) of model efficiency criteria and parameter values differed. An increasing number of calibration repetitions tend to increase the ranges of model efficiency criteria during model validation, particularly for the runoff volume error and snow error, which were not directly used in model calibration. Comparison of model efficiencies in climate conditions that varied among the five periods documented changes in model performance in different periods but the difference between 10 and 500 calibration repetitions did not change much between the selected time periods. The results suggest that ten repetitions of model calibrations provided the same median of model efficiency criteria as a greater number of calibration repetitions and model parameter variability and uncertainty were smaller.

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