Quantum Computing for Analyzing CD4 Lymphocytes and Antiretroviral Therapy
Check if Coefficients of a Qubit State Object are Complex Numbers
Calculate the Conjugate Transpose of a Quantum State
Create Interactions from CD4 and Viral Load Data
Estimate Payoff Parameters for HIV Phenotype Interactions
Interaction Classification for Viral Load and CD4 Differences
Mean Squared Errors method for the InteractionClassification class
Mean Squared Errors for Interaction Classification
Find Nearest Payoff
Normalize Check Function for qstate Class Object
Generate Payoff List Based on Quantum Gates and Parameters
Calculate Final State and Payoffs in Quantum Game
Plot Interaction Differences
Plot InteractionClassification Clusters
Print Summary of CD4 and Viral Load Differences
Print Method for InteractionClassification Objects
Create a normalized pure quantum state for a 1-qubit system.
Create a normalized pure quantum state for a 2-qubit system.
qvirus: Quantum Computing for Analyzing CD4 Lymphocytes and Antiretrov...
Simulate Entanglement Evolution
Create Six Important States on the Bloch Sphere
Summary Method for Interaction Class Objects
Summarize Interaction Classification Results
Summarize Payoffs
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.