Francesca Incardona
Francesca Incardona
Informa - Euresist
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Cited by
Selecting anti-HIV therapies based on a variety of genomic and clinical factors
M Rosen-Zvi, A Altmann, M Prosperi, E Aharoni, H Neuvirth, ...
Bioinformatics 24 (13), i399-i406, 2008
Comparison of HIV-1 genotypic resistance test interpretation systems in predicting virological outcomes over time
D Frentz, CAB Boucher, M Assel, A De Luca, M Fabbiani, F Incardona, ...
PloS one 5 (7), 2010
Comparison of classifier fusion methods for predicting response to anti HIV-1 therapy
A Altmann, M Rosen-Zvi, M Prosperi, E Aharoni, H Neuvirth, E Schülter, ...
PloS one 3 (10), 2008
Prediction of response to antiretroviral therapy by human experts and by the EuResist data‐driven expert system (the EVE study)
M Zazzi, R Kaiser, A Sönnerborg, D Struck, A Altmann, M Prosperi, ...
HIV medicine 12 (4), 211-218, 2011
Predicting response to antiretroviral treatment by machine learning: the EuResist project
M Zazzi, F Incardona, M Rosen-Zvi, M Prosperi, T Lengauer, A Altmann, ...
Intervirology 55 (2), 123-127, 2012
Detection of drug resistance mutations at low plasma HIV-1 RNA load in a European multicentre cohort study
MCF Prosperi, N Mackie, S Di Giambenedetto, M Zazzi, R Camacho, ...
Journal of antimicrobial chemotherapy 66 (8), 1886-1896, 2011
Advantages of predicted phenotypes and statistical learning models in inferring virological response to antiretroviral therapy from HIV genotype
A Altmann, T Sing, H Vermeiren, B Winters, E Van Craenenbroeck, ...
Antiviral Therapy 14 (2), 273-283, 2009
Stochastic modelling of genotypic drug-resistance for human immunodeficiency virus towards long-term combination therapy optimization
MCF Prosperi, R D'Autilia, F Incardona, A De Luca, M Zazzi, G Ulivi
Bioinformatics 25 (8), 1040-1047, 2009
Future challenges and recommendations
V Jones, F Incardona, C Tristram, S Virtuoso, A Lymberis
M-Health, 267-270, 2006
Drug resistance testing through remote genotyping and predicted treatment options in human immunodeficiency virus type 1 infected Tanzanian subjects failing first or second …
J Svärd, S Mugusi, D Mloka, U Neogi, G Meini, F Mugusi, F Incardona, ...
PloS one 12 (6), 2017
PhyloGeoTool: interactively exploring large phylogenies in an epidemiological context
P Libin, E Vanden Eynden, F Incardona, A Nowé, A Bezenchek, ...
Bioinformatics 33 (24), 3993-3995, 2017
Efficacy of etravirine combined with darunavir or other ritonavir‐boosted protease inhibitors in HIV‐1‐infected patients: an observational study using pooled E uropean cohort data
J Vingerhoets, V Calvez, P Flandre, AG Marcelin, ...
HIV medicine 16 (5), 297-306, 2015
History-alignment models for bias-aware prediction of virological response to HIV combination therapy
J Bogojeska, D Stockel, M Zazzi, R Kaiser, F Incardona, M Rosen-Zvi, ...
Artificial Intelligence and Statistics, 118-126, 2012
Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes
SY Rhee, JL Blanco, TF Liu, I Pere, R Kaiser, M Zazzi, F Incardona, ...
AIDS research and therapy 9 (1), 13, 2012
Future Challenges and Recommendations, IN M-Health: Emerging Mobile Health Systems, Robert H. Istepanian, Swamy Laxminarayan, Constantinos S. Pattichis, Editors
V Jones, F Incardona, C Tristram, S Virtuoso, A Lymberis
Springer, 2006
A21 HIV-1 sub-subtype F1 outbreak among MSM in Belgium
L Vinken, K Fransen, AC Pineda-Peña, I Alexiev, C Balotta, L Debaisieux, ...
Virus evolution 3 (suppl_1), 2017
HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure
RZ Sangeda, K Theys, G Beheydt, SY Rhee, K Deforche, J Vercauteren, ...
Infection, Genetics and Evolution 19, 349-360, 2013
EuResist: exploration of multiple modeling techniques for prediction of response to treatment
M Zazzi, E Aharoni, A Altmann, F Baszó, P Bidgood, G Borgulya, ...
Proceedings of the 5th European HIV Drug Resistance Workshop, 2007
Keeping models that predict response to antiretroviral therapy up-to-date: fusion of pure data-driven approaches with rules-based methods
A Altmann, A Thielen, D Frentz, KV Laethem, L Bracciale, F Incardona
Rev Antivir Ther 1, A92, 2009
Integration of viral genomics with clinical data to predict response to anti-HIV treatment
E Aharoni, A Altmann, G Borgulya, R D’AUTILIA, F INCARDONA, ...
IST-Africa conference proceedings. Dublin: IIMC International Information …, 2007
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