mse.payoffs

Computes the mean squared error (MSE) between observed CD4 and viral load differences
and their corresponding predicted payoff values within each interaction 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.payoffs function

<dl><dt>object</dt>
<dd>An object of class <code>payoffs</code>.</dd>
<dt>...</dt>
<dd>Additional arguments passed to other methods (currently not used).</dd></dl>

Arguments

Mean Squared Errors for Payoff Predictions — mse.payoffs

<dl>

<dt>object</dt>
<dd>An object of class <code>payoffs</code>.</dd>


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

</dl>

mse.payoffs: Mean Squared Errors for Payoff Predictions

Description

Usage

Arguments