113 related articles for article (PubMed ID: 21785323)
1. The development of an expert system to predict virological response to HIV therapy as part of an online treatment support tool.
Revell AD; Wang D; Boyd MA; Emery S; Pozniak AL; De Wolf F; Harrigan R; Montaner JS; Lane C; Larder BA;
AIDS; 2011 Sep; 25(15):1855-63. PubMed ID: 21785323
[TBL] [Abstract][Full Text] [Related]
2. A comparison of three computational modelling methods for the prediction of virological response to combination HIV therapy.
Wang D; Larder B; Revell A; Montaner J; Harrigan R; De Wolf F; Lange J; Wegner S; Ruiz L; Pérez-Elías MJ; Emery S; Gatell J; D'Arminio Monforte A; Torti C; Zazzi M; Lane C
Artif Intell Med; 2009 Sep; 47(1):63-74. PubMed ID: 19524413
[TBL] [Abstract][Full Text] [Related]
3. The development of artificial neural networks to predict virological response to combination HIV therapy.
Larder B; Wang D; Revell A; Montaner J; Harrigan R; De Wolf F; Lange J; Wegner S; Ruiz L; Pérez-Elías MJ; Emery S; Gatell J; Monforte AD; Torti C; Zazzi M; Lane C
Antivir Ther; 2007; 12(1):15-24. PubMed ID: 17503743
[TBL] [Abstract][Full Text] [Related]
4. Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment.
Prosperi MC; Altmann A; Rosen-Zvi M; Aharoni E; Borgulya G; Bazso F; Sönnerborg A; Schülter E; Struck D; Ulivi G; Vandamme AM; Vercauteren J; Zazzi M;
Antivir Ther; 2009; 14(3):433-42. PubMed ID: 19474477
[TBL] [Abstract][Full Text] [Related]
5. Study of the impact of HIV genotypic drug resistance testing on therapy efficacy.
Van Vaerenbergh K
Verh K Acad Geneeskd Belg; 2001; 63(5):447-73. PubMed ID: 11813503
[TBL] [Abstract][Full Text] [Related]
6. Construction, training and clinical validation of an interpretation system for genotypic HIV-1 drug resistance based on fuzzy rules revised by virological outcomes.
De Luca A; Vendittelli M; Baldini F; Di Giambenedetto S; Trotta MP; Cingolani A; Bacarelli A; Gori C; Perno CF; Antinori A; Ulivi G
Antivir Ther; 2004 Aug; 9(4):583-93. PubMed ID: 15456090
[TBL] [Abstract][Full Text] [Related]
7. Rules-based HIV-1 genotypic resistance interpretation systems predict 8 week and 24 week virological antiretroviral treatment outcome and benefit from drug potency weighting.
Zazzi M; Prosperi M; Vicenti I; Di Giambenedetto S; Callegaro A; Bruzzone B; Baldanti F; Gonnelli A; Boeri E; Paolini E; Rusconi S; Giacometti A; Maggiolo F; Menzo S; De Luca A;
J Antimicrob Chemother; 2009 Sep; 64(3):616-24. PubMed ID: 19620134
[TBL] [Abstract][Full Text] [Related]
8. Impact of genotypic resistance testing on selection of salvage regimen in clinical practice.
Haupts S; Ledergerber B; Böni J; Schüpbach J; Kronenberg A; Opravil M; Flepp M; Speck RF; Grube C; Rentsch K; Weber R; Günthard HF;
Antivir Ther; 2003 Oct; 8(5):443-54. PubMed ID: 14640392
[TBL] [Abstract][Full Text] [Related]
9. A genotypic drug resistance interpretation algorithm that significantly predicts therapy response in HIV-1-infected patients.
Van Laethem K; De Luca A; Antinori A; Cingolani A; Perna CF; Vandamme AM
Antivir Ther; 2002 Jun; 7(2):123-9. PubMed ID: 12212924
[TBL] [Abstract][Full Text] [Related]
10. The use of drug resistance algorithms and genotypic inhibitory quotient in prediction of lopinavir-ritonavir treatment response in human immunodeficiency virus type 1 protease inhibitor-experienced patients.
Maillard A; Chapplain JM; Tribut O; Bentué-Ferrer D; Tattevin P; Arvieux C; Michelet C; Ruffault A
J Clin Virol; 2007 Feb; 38(2):131-8. PubMed ID: 17208042
[TBL] [Abstract][Full Text] [Related]
11. Advantages of predicted phenotypes and statistical learning models in inferring virological response to antiretroviral therapy from HIV genotype.
Altmann A; Sing T; Vermeiren H; Winters B; Van Craenenbroeck E; Van der Borght K; Rhee SY; Shafer RW; Schülter E; Kaiser R; Peres Y; Sönnerborg A; Fessel WJ; Incardona F; Zazzi M; Bacheler L; Van Vlijmen H; Lengauer T
Antivir Ther; 2009; 14(2):273-83. PubMed ID: 19430102
[TBL] [Abstract][Full Text] [Related]
12. Predictive factors for immunological and virological endpoints in Thai patients receiving combination antiretroviral treatment.
Srasuebkul P; Ungsedhapand C; Ruxrungtham K; Boyd MA; Phanuphak P; Cooper DA; Law MG
HIV Med; 2007 Jan; 8(1):46-54. PubMed ID: 17305932
[TBL] [Abstract][Full Text] [Related]
13. Comparison of tests and procedures to build clinically relevant genotypic scores: application to the Jaguar study.
Flandre P; Marcelin AG; Pavie J; Shmidely N; Wirden M; Lada O; Bernard MC; Molina JM; Calvez V
Antivir Ther; 2005; 10(4):479-87. PubMed ID: 16038473
[TBL] [Abstract][Full Text] [Related]
14. Clinical cut-offs for HIV-1 phenotypic resistance estimates: update based on recent pivotal clinical trial data and a revised approach to viral mixtures.
Winters B; Van Craenenbroeck E; Van der Borght K; Lecocq P; Villacian J; Bacheler L
J Virol Methods; 2009 Dec; 162(1-2):101-8. PubMed ID: 19654022
[TBL] [Abstract][Full Text] [Related]
15. Virologic therapy response significantly correlates with the number of active drugs as evaluated using a LiPA HIV-1 resistance scoring system.
Ziermann R; Celis L; Derdelinckx I; Lambert C; Veeck J; Rizzo MG; Vanderborght B; Zissis G; Clumeck N; Fransen K; Vaira D; Hendricks D; Van Laethem K; Vandamme AM; Schmit JC; Knechten H; De Luca A; Louwagie J; Segers P; De Boeck K; Pottel H; De Brauwer A; Hulstaert F
J Clin Virol; 2004 Dec; 31 Suppl 1():S7-15. PubMed ID: 15567089
[TBL] [Abstract][Full Text] [Related]
16. Genotypic resistance and HIV-1 subtype in Brazilian children on dual and triple combination therapy.
Machado ES; Lambert JS; Watson DC; Afonso AO; da Cunha SM; Nogueira SA; Caride E; Oliveira RH; Sill AM; DeVico A; Tanuri A
J Clin Virol; 2004 May; 30(1):24-31. PubMed ID: 15072750
[TBL] [Abstract][Full Text] [Related]
17. Inhibitory quotient as a prognostic factor of response to a salvage antiretroviral therapy containing ritonavir-boosted saquinavir. The CIVSA Study.
Mallolas J; Blanco J; Labarga P; Vergara A; Ocampo A; Sarasa M; Arnedo M; López-Púa Y; García J; Juega J; Guelar A; Terrón A; Dalmau D; García I; Zárraga M; Martínez E; Carné X; Pumarola T; Escayola R; Gatell J
HIV Med; 2007 May; 8(4):226-33. PubMed ID: 17461850
[TBL] [Abstract][Full Text] [Related]
18. Efficacy, safety and predictive factors of virological success of a boosted amprenavir-based salvage regimen in heavily antiretroviral-experienced HIV-1-infected patients.
Clevenbergh P; Boulmé R; Kirstetter M; Dellamonica P
HIV Med; 2004 Jul; 5(4):284-8. PubMed ID: 15236618
[TBL] [Abstract][Full Text] [Related]
19. Drug resistance genotypes predict response to amprenavir-containing regimens in highly drug-experienced HIV-1-infected patients.
Sabin CA; Wilkins E; Murphy M; Fisher M; de Ruiter A; Easterbrook PJ; Leen C; Vlahakis E; Cane PA; Li X; Pillay D;
Antivir Ther; 2003 Aug; 8(4):301-8. PubMed ID: 14518699
[TBL] [Abstract][Full Text] [Related]
20. Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings.
Revell AD; Wang D; Wood R; Morrow C; Tempelman H; Hamers RL; Alvarez-Uria G; Streinu-Cercel A; Ene L; Wensing AM; DeWolf F; Nelson M; Montaner JS; Lane HC; Larder BA;
J Antimicrob Chemother; 2013 Jun; 68(6):1406-14. PubMed ID: 23485767
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
