Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

González, Roberto J.; Coutinho, S.; Santos, Rita Maria Zorzenon dos; Figueirêdo, Pedro Hugo de

doi:10.1016/j.physa.2013.05.056

Cited by 27 publications

(25 citation statements)

References 64 publications

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“…compared the results obtained from their CA model with clinical data which had been published in some of the authentic articles [15]. So in present work in order to validation of the results obtained from proposed CA model, we also apply the clinical data that had been used by Gonzales et al In [35] nine patients were se- happened at 220 th week.…”

Section: Validating the Obtained Results From Ca Model Through Comparmentioning

confidence: 98%

“…Santos was the basis of many articles published in the field of modeling the dynamics of HIV infection in lymphoid tissue using CA approach [13] [14] [15] [16].…”

Section: Most Of Researchers Have Used Models With Ordinary Differentmentioning

confidence: 99%

“…This type of healthy cell becomes a normal healthy cell for the next iteration [15] [16]. If an A1 cell is not identified by the immune system cells, it releases a new infectious HIV from within itself with probability of P HIV-PR [16] [18] [19].…”

Section: The Rules Of Proposed Ca Modelmentioning

confidence: 99%

“…0.0005 [14] P PI & P RTI The effectiveness of PI and RTI antiretroviral drugs Varies between 0 to 0.9 [15] …”

Section: The Parameters Of Proposed Modelmentioning

confidence: 99%

“…To consider these inputs, we used a parameter named effectiveness as P RTI and P PI for RTI and PI antiretroviral drugs, respectively [15] …”

Section: The Inputs and Outputs Of Proposed Modelmentioning

confidence: 99%

See 4 more Smart Citations

Providing a Therapeutic Scheduling for HIV Infected Individuals with Genetic Algorithms Using a Cellular Automata Model of HIV Infection in the Peripheral Blood Stream

Golpayegani¹,

Jafari‬²,

Dabanloo³

2017

JBiSE

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The aim of this study is to develop two-dimensional cellular automata model of HIV infection that depicts the dynamics involved in the interactions between acquired immune system and HIV infection in the peripheral blood stream. The appropriate biological rules of cellular automata model have been extracted from expert knowledge and the model has been simulated with determined initial conditions. Obtained results have been validated through comparing with the accepted AIDS reference curve. The new rules and states were added to the proposed model to show the effects of applying combined antiretroviral therapy. Our results showed that by applying RTI and PI drugs with maximum drug effectiveness, comparing with cases in which no treatment was applied, the steady state concentrations of healthy (infected) CD 4 + T cells were increased (decreased) 53% (41%). Also, the use of cART with maximum drug effectiveness led to a 69% reduction in the steady state level of viral load. At this time, obtained results have been validated through comparing with available clinical data. Our results showed good agreement with both reference curve and the clinical data. In the second phase of this study, by applying genetic algorithms, a therapeutic schedule has been provided that its use, while maintaining the quality of the treatment, leads to a 47% reduction in both drug dosage and the side effects of antiretroviral drugs.

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Section: Validating the Obtained Results From Ca Model Through Comparmentioning

confidence: 98%

“…Santos was the basis of many articles published in the field of modeling the dynamics of HIV infection in lymphoid tissue using CA approach [13] [14] [15] [16].…”

Section: Most Of Researchers Have Used Models With Ordinary Differentmentioning

confidence: 99%

Section: The Rules Of Proposed Ca Modelmentioning

confidence: 99%

“…0.0005 [14] P PI & P RTI The effectiveness of PI and RTI antiretroviral drugs Varies between 0 to 0.9 [15] …”

Section: The Parameters Of Proposed Modelmentioning

confidence: 99%

“…To consider these inputs, we used a parameter named effectiveness as P RTI and P PI for RTI and PI antiretroviral drugs, respectively [15] …”

Section: The Inputs and Outputs Of Proposed Modelmentioning

confidence: 99%

See 3 more Smart Citations

Providing a Therapeutic Scheduling for HIV Infected Individuals with Genetic Algorithms Using a Cellular Automata Model of HIV Infection in the Peripheral Blood Stream

Golpayegani¹,

Jafari‬²,

Dabanloo³

2017

JBiSE

View full text Add to dashboard Cite

show abstract

Error dynamic shaping in HIV optimized drug delivery control

Fatemi

Mahmoodian

2020

Evolving Systems

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Optimal sigmoid nonlinear stochastic control of HIV-1 infection based on bacteria foraging optimization method

Abharian

Sarabi

Yomi

2014

Biomedical Signal Processing and Control

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Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

Cited by 27 publications

References 64 publications

Providing a Therapeutic Scheduling for HIV Infected Individuals with Genetic Algorithms Using a Cellular Automata Model of HIV Infection in the Peripheral Blood Stream

Providing a Therapeutic Scheduling for HIV Infected Individuals with Genetic Algorithms Using a Cellular Automata Model of HIV Infection in the Peripheral Blood Stream

Error dynamic shaping in HIV optimized drug delivery control

Optimal sigmoid nonlinear stochastic control of HIV-1 infection based on bacteria foraging optimization method

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