Predicting response to antiretroviral treatment by machine learning: The euresist project

Intervirology

Volumn 55, Issue 2, 2012, Pages 123-127

  Zazzi, Maurizio ^a   Incardona, Francesca ^b   Rosen Zvi, Michal ^c   Prosperi, Mattia ^a   Lengauer, Thomas ^d   Altmann, Andre ^d   Sonnerborg, Anders ^f   Lavee, Tamar ^c   Schülter, Eugen ^e   Kaiser, Rolf ^e  

^a UNIVERSITY OF SIENA   (Italy)

^b Informa Srl   (Italy)

^c IBM HAIFA RESEARCH LAB   (Israel)

^d International Max Planck Research School   (Germany)

^e UNIVERSITY OF COLOGNE   (Germany)

^f KAROLINSKA INSTITUTE   (Sweden)

Author keywords

Antiretroviral therapy; EuResist; HIV resistance; Interpretation system; Machine learning

Indexed keywords

ANTIRETROVIRUS AGENT; DARUNAVIR; ETRAVIRINE; TIPRANAVIR;

AGE; ANTIVIRAL RESISTANCE; ANTIVIRAL THERAPY; ARTICLE; CASE BASED REASONING; CD4 LYMPHOCYTE COUNT; CLINICAL DECISION MAKING; DECISION SUPPORT SYSTEM; DRUG RESPONSE; ETHNICITY; EURESIST ENGINE; FOLLOW UP; FUZZY LOGIC; GENOTYPE; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; MACHINE LEARNING; MEDICAL HISTORY; PREDICTION; PRIORITY JOURNAL; PROBABILITY; QUALITY CONTROL; RANDOM FOREST; REFERENCE DATABASE; SUPPORT VECTOR MACHINE; VIRUS LOAD;

ANTI-HIV AGENTS; ARTIFICIAL INTELLIGENCE; DRUG RESISTANCE, VIRAL; GENOTYPE; HIV INFECTIONS; HIV-1; HUMANS; MICROBIAL SENSITIVITY TESTS;

EID: 84856433482     PISSN: 03005526     EISSN: 14230100     Source Type: Journal    
DOI: 10.1159/000332008     Document Type: Article

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