Table 2.

Nomenclature and parameters of the developed COVID-19 diagnosis model.

Symbol	Description
$\mathit{F}$	Feature node
$\mathit{FV}$	Feature vector
$\mathit{FG}$	Feature graph
$\mathit{E}$	Link between original features
$\mathit{n}$	Number of initial features
$\mathit{Sim}(\mathit{i},\mathit{j})$	Similarity between features ${\mathit{f}}_{\mathit{i}}$ and ${\mathit{f}}_{\mathit{j}}$
$\mathit{F}{\mathit{V}}_{\mathit{i}}$	Feature Vector ${\mathit{f}}_{\mathit{i}}$
$\overline{\mathit{F}{\mathit{V}}_{\mathit{i}}}$	Average of feature vector $\mathit{F}{\mathit{V}}_{\mathit{i}}$
$\mathit{P}$	Set of dataset samples
$\overline{\mathit{Sim}}$	Average of all the calculated similarities
$\mathit{\sigma }$	Variance of all the calculated similarities
$\mathit{IV}\left({\mathit{f}}_{\mathit{i}}\right)$	Importance Value of feature ${\mathit{f}}_{\mathit{i}}$
$\mathit{FS}\left({\mathit{f}}_{\mathit{i}}\right)$	Fisher Score of features ${\mathit{f}}_{\mathit{i}}$
$\mathit{NC}\left({\mathit{f}}_{\mathit{i}}\right)$	Node Centrality of feature ${\mathit{f}}_{\mathit{i}}$
$\mathit{V}$	Set of all classes in a dataset (i.e. Positive and Negative)
${\mathit{n}}_{\mathit{v}}$	Number of patterns on the class
$\overline{\mathit{F}{\mathit{V}}_{\mathit{k}}^{\mathit{v}}}$	Average of feature vector $F_k$ on class $\mathit{v}$
$\mathit{\sigma }\left(\mathit{F}{\mathit{V}}_{\mathit{k}}\right)$	Variance of feature vector $F_k$ on class $\mathit{v}$
${\mathit{E}}_{\mathit{L}}$	Laplacian Energy
$\overline{{\mathit{f}}_{\mathit{k}}}$	Average value of all the samples related to the feature ${\mathit{f}}_{\mathit{k}}$
$\mathit{V}$	Set of all classes in a dataset (i.e. Positive and Negative)
${\mathit{n}}_{\mathit{v}}$	Number of samples on the class $\mathit{v}$
$\mathit{\sigma }\left({\mathit{f}}_{\mathit{k}}\right)$	Variance and average of feature ${\mathit{f}}_{\mathit{k}}$ on class $\mathit{v}$
$\overline{{\mathit{f}}_{\mathit{k}}^{\mathit{v}}}$	Average of feature ${\mathit{f}}_{\mathit{k}}$ on class $\mathit{v}$
$\mathbf{T}$	Decision tree
$\phi$	Set of rules in Decision tree
$\mathit{K}$	Number of trees in decision forest