Prediction of skin penetration using machine learning methods

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2008, Pages 1049-1054

  Sun, Yi ^a   Moss, Gary P ^a   Prapopoulou, Maria ^a   Adams, Rod ^a   Brown, Marc B ^a   Davey, Neil ^a  

^a UNIVERSITY OF HERTFORDSHIRE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPOUND FEATURES; DONOR GROUPS; GAUSSIAN PROCESS REGRESSION; GAUSSIAN PROCESSES; HYDROGEN BONDINGS; LIPOPHILICITY; MACHINE LEARNING METHODS; MIXTURE OF EXPERTS; NEAREST-NEIGHBOUR; PERMEABILITY COEFFICIENTS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS; SINGLE LAYER; SKIN PATCH; SKIN PENETRATION; SKIN PERMEABILITY; SOLUBILITY PARAMETERS;

CAPILLARITY; CONTROLLED DRUG DELIVERY; FACE RECOGNITION; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); HYDRAULIC CONDUCTIVITY; HYDROGEN; HYDROGEN BONDS; INFORMATION MANAGEMENT; MINING; MOLECULAR WEIGHT;

SKIN;

EID: 67049097965     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2008.97     Document Type: Conference Paper

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