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Table 2 Results of laboratory tests for a simple threshold-based model Hand Accuracy Sensitivity Specificity Left 76.3%83.5%52.1%1% Right 77.9%87.3%% 62.5% When tuning the model parameters, sensitivity was given a priority over specificity, as it is in our interest to detect all falls, even if it results in some additional false alarms.
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Visible symptoms are described and illustrated and tables of relative sensitivity are given and their limitations discussed.
Sensitivity is given by Sensitivity = frac{{number,of,TP}}{{number,of,TP + number,of,FN}}.
Sensitivity is given as nm/RIU, where RIU denotes refractive index units.
The effect of permeable linker layer on the sensitivity is given elsewhere [19].
Material sensitivity is given in terms of work function variation induced by gas species adsorption.
Additional discussion of parameter selection and sensitivity is given in the context of an example which concerns prediction of breast tumour status utilizing high-dimensional gene expression data; the example demonstrates the exploratory/explanatory uses of such models as well as their primary utility in prediction.
If we let H be the event of a given patient having the disease, and E be the event of her testing positive for it, then the test's specificity and sensitivity are given by the likelihoods PH(E) and P~H ~E), respectively, and the "baseline" prevalence of the disease in the population is P(H).
Several ideas to improve this overall sensitivity are given below.
>> The per patient sensitivity is given in Table 6.
Likelihood Figure 14: The pooled sensitivity is given by 1/1+exp (-μ1) and pooled specificity as 1/1+exp (μ2).
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