Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment

Antiviral Therapy

Volumn 14, Issue 3, 2009, Pages 433-442

  Prosperi, Mattia C F ^a,b   Altmann, Andre ^c   Rosen Zvi, Michal ^d   Aharoni, Ehud ^d   Borgulya, Gabor ^e   Bazso, Fulop ^e   Sönnerborg, Anders ^f   Schülter, Eugen ^g   Struck, Daniel ^h   Ulivi, Giovanni ^a   Vandamme, Anne Mieke ⁱ   Vercauteren, Jurge ⁱ   Zazzi, Maurizio ^j  

^a ROMA TRE UNIVERSITY   (Italy)

^b Informa   (Italy)

^c MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

^d IBM HAIFA RESEARCH LAB   (Israel)

^e INSTITUTE OF EXPERIMENTAL MEDICINE   (Hungary)

^f KAROLINSKA INSTITUTE   (Sweden)

^g UNIVERSITY OF COLOGNE   (Germany)

^h LUXEMBOURG INSTITUTE OF HEALTH   (Luxembourg)

ⁱ REGA INSTITUTE FOR MEDICAL RESEARCH   (Belgium)

^j UNIVERSITY OF SIENA   (Italy)

more..

Author keywords

[No Author keywords available]

Indexed keywords

ANTIVIRAL THERAPY; AREA UNDER THE CURVE; ARTICLE; COMPUTER PREDICTION; DECISION SUPPORT SYSTEM; DRUG RESPONSE; HUMAN IMMUNODEFICIENCY VIRUS 1 INFECTION; INTERMETHOD COMPARISON; LEARNING ALGORITHM; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; NONLINEAR SYSTEM; PREDICTION; PRIORITY JOURNAL; REFERENCE DATABASE; STATISTICAL ANALYSIS; STATISTICAL MODEL; VIRUS GENOME;

ADULT; ANTI-HIV AGENTS; ARTIFICIAL INTELLIGENCE; DATABASES, FACTUAL; FEMALE; HIV INFECTIONS; HIV-1; HUMANS; LOGISTIC MODELS; MALE; MODELS, STATISTICAL; TREATMENT OUTCOME; VIRAL LOAD;

EID: 67649191714     PISSN: 13596535     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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