mse.InteractionClassification

Mean squared errors (MSE) for viral load differences
and CD4 count differences by comparing the actual values with the group means
from the classification.

Resources, tutorials, and code snippets dedicated to exploring the intersection of quantum computing and artificial intelligence (AI) in the context of analyzing Cluster of Differentiation 4 (CD4) lymphocytes and optimizing antiretroviral therapy (ART) for human immunodeficiency virus (HIV). With the emergence of quantum artificial intelligence and the development of small-scale quantum computers, there's an unprecedented opportunity to revolutionize the understanding of HIV dynamics and treatment strategies. This project leverages the R package 'qsimulatR' (Ostmeyer and Urbach, 2023, <https://CRAN.R-project.org/package=qsimulatR>), a quantum computer simulator, to explore these applications in quantum computing techniques, addressing the challenges in studying CD4 lymphocytes and enhancing ART efficacy.

Juan Pablo Acuña González

qvirus

Quantum Computing for Analyzing CD4 Lymphocytes and
Antiretroviral Therapy

mse.InteractionClassification function

<dl><dt>object</dt>
<dd>An object of class <code>InteractionClassification</code> containing
the classified data and clustering results.</dd>
<dt>...</dt>
<dd>Additional arguments passed to other methods (currently not used).</dd></dl>

Arguments

Mean Squared Errors for Interaction Classification — mse.InteractionClassification

<dl>

<dt>object</dt>
<dd>An object of class <code>InteractionClassification</code> containing
the classified data and clustering results.</dd>


<dt>...</dt>
<dd>Additional arguments passed to other methods (currently not used).</dd>

</dl>

mse.InteractionClassification: Mean Squared Errors for Interaction Classification

Description

Usage

Arguments