Dealing with sparse data in predicting outcomes of HIV combination therapies

Bioinformatics

Volumn 26, Issue 17, 2010, Pages 2085-2092

  Bogojeska, Jasmina ^a   Bickel, Steffen ^b   Altmann, André ^a   Lengauer, Thomas ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

^b NONE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN IMMUNODEFICIENCY VIRUS;

ANTI HUMAN IMMUNODEFICIENCY VIRUS AGENT;

ARTICLE; ARTIFICIAL INTELLIGENCE; DRUG COMBINATION; GENETICS; GENOTYPE; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; STATISTICAL MODEL; TREATMENT OUTCOME; VIROLOGY;

ANTI-HIV AGENTS; ARTIFICIAL INTELLIGENCE; DRUG THERAPY, COMBINATION; GENOTYPE; HIV; HIV INFECTIONS; HUMANS; LOGISTIC MODELS; TREATMENT OUTCOME;

EID: 77955892900     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btq361     Document Type: Article

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