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pro vyhledávání: '"Balayla, Jacques"'
Autor:
Balayla, Jacques
In this manuscript, we present various proposed methods estimate the prevalence of disease, a critical prerequisite for the adequate interpretation of screening tests. To address the limitations of these approaches, which revolve primarily around the
Externí odkaz:
http://arxiv.org/abs/2401.04086
Autor:
Balayla, Jacques
We define the information threshold as the point of maximum curvature in the prior vs. posterior Bayesian curve, both of which are described as a function of the true positive and negative rates of the classification system in question. The nature of
Externí odkaz:
http://arxiv.org/abs/2206.02266
Autor:
Balayla, Jacques
The accuracy of binary classification systems is defined as the proportion of correct predictions - both positive and negative - made by a classification model or computational algorithm. A value between 0 (no accuracy) and 1 (perfect accuracy), the
Externí odkaz:
http://arxiv.org/abs/2112.13289
Publikováno v:
In Journal of Obstetrics and Gynaecology Canada April 2024 46(4)
Autor:
Balayla, Jacques
In previous work by this author, the screening paradox - the loss of predictive power of screening tests over time $t$ - was mathematically formalized using Bayesian theory. Where $J$ is Youden's statistic, $b$ is the specificity of the screening tes
Externí odkaz:
http://arxiv.org/abs/2104.07806
Autor:
Balayla, Jacques
From the fundamental theorem of screening (FTS) we obtain the following mathematical relationship relaying the pre-test probability of disease $\phi$ to the positive predictive value $\rho(\phi)$ of a screening test: $\displaystyle\lim_{\varepsilon \
Externí odkaz:
http://arxiv.org/abs/2012.07066
Autor:
Balayla, Jacques
Bayes' Theorem imposes inevitable limitations on the accuracy of screening tests by tying the test's predictive value to the disease prevalence. The aforementioned limitation is independent of the adequacy and make-up of the test and thus implies inh
Externí odkaz:
http://arxiv.org/abs/2011.06032
Autor:
Balayla, Jacques
Using Bayes' Theorem, we derive generalized equations to determine the positive and negative predictive value of screening tests undertaken sequentially. Where a is the sensitivity, b is the specificity, $\phi$ is the pre-test probability, the combin
Externí odkaz:
http://arxiv.org/abs/2007.13046
Autor:
Balayla, Jacques
Bayes' Theorem confers inherent limitations on the accuracy of screening tests as a function of disease prevalence. We have shown in previous work that a testing system can tolerate significant drops in prevalence, up until a certain well-defined poi
Externí odkaz:
http://arxiv.org/abs/2006.11641
Autor:
Balayla, Jacques
The relationship between a screening tests' positive predictive value, $\rho$, and its target prevalence, $\phi$, is proportional - though not linear in all but a special case. In consequence, there is a point of local extrema of curvature defined on
Externí odkaz:
http://arxiv.org/abs/2006.00398