A. Revell

发表

Modelling response to HIV therapy without a genotype: an argument for viral load monitoring in resource-limited settings.

A. Wensing, B. Larder, A. Revell, 2010, The Journal of antimicrobial chemotherapy.

Clinical evaluation of the potential utility of computational modeling as an HIV treatment selection tool by physicians with considerable HIV experience.

B. Gazzard, B. Larder, J. Metcalf, 2011, AIDS patient care and STDs.

The Development of Artificial Neural Networks to Predict Virological response to Combination HIV Therapy

Brendan Larder, Lidia Ruiz, Andrew Revell, 2007, Antiviral therapy.

Potential Impact of a Free Online HIV Treatment Response Prediction System for Reducing Virological Failures and Drug Costs after Antiretroviral Therapy Failure in a Resource-Limited Setting

B. Larder, J. Montaner, A. Pozniak, 2013, BioMed research international.

The development of an expert system to predict virological response to HIV therapy as part of an online treatment support tool

B. Larder, J. Montaner, S. Emery, 2011, AIDS.

Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings.

A. Wensing, B. Larder, R. Wood, 2013, The Journal of antimicrobial chemotherapy.

2021 update to HIV-TRePS: a highly flexible and accurate system for the prediction of treatment response from incomplete baseline information in different healthcare settings.

B. Gazzard, R. Kaiser, B. Larder, 2021, The Journal of antimicrobial chemotherapy.

Predicting Virological Response to HIV Treatment Over Time: A Tool for Settings With Different Definitions of Virological Response

B. Larder, J. Montaner, B. Clotet, 2019, Journal of acquired immune deficiency syndromes.

2018 update to the HIV-TRePS system: the development of new computational models to predict HIV treatment outcomes, with or without a genotype, with enhanced usability for low-income settings

Dechao Wang, Shanmugam Saravanan, John Baxter, 2018, The Journal of antimicrobial chemotherapy.

A World of HIV Treatment Experience Freely Available at the Click of a Mouse

B. Gazzard, A. Revell, H. Lane, 2014 .

Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

B. Larder, P. Reiss, S. Emery, 2016, Southern African journal of HIV medicine.

An update to the HIV-TRePS system: the development of new computational models that do not require a genotype to predict HIV treatment outcomes.

A. Wensing, B. Larder, J. Montaner, 2014, The Journal of antimicrobial chemotherapy.

A Comparison of Three Computational Modelling Methods for the Prediction of Virological Response to Combination Hiv Therapy Author's Personal Copy

Brendan Larder, Dechao Wang, Lidia Ruiz, 2022 .

An update to the HIV-TRePS system: the development and evaluation of new global and local computational models to predict HIV treatment outcomes, with or without a genotype.

Peter Reiss, Hugo Tempelman, Andrew D Revell, 2016, The Journal of antimicrobial chemotherapy.

A comparison of three computational modelling methods for the prediction of virological response to combination HIV therapy

A. d’Arminio Monforte, B. Larder, J. Montaner, 2009, Artif. Intell. Medicine.

The use of computational models to predict response to HIV therapy for clinical cases in Romania.

B. Larder, J. Montaner, M. Youle, 2012, Germs.