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Psychotropic drug classification based on sleep–wake behaviour of rats
Author(s) -
Wouters Kristien,
Ahnaou Abdellah,
Abrahantes Jose Cortinas,
Molenberghs Geert,
Geys Helena,
Bijnens Luc,
Drinkenburg Wilhelmus H. I. M.
Publication year - 2007
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2007.00575.x
Subject(s) - sketch , class (philosophy) , linear discriminant analysis , computer science , artificial intelligence , zoom , machine learning , psychotropic drug , set (abstract data type) , data set , drug class , pattern recognition (psychology) , data mining , drug , psychology , psychiatry , algorithm , programming language , petroleum engineering , engineering , lens (geology)
Summary. The aim of the paper is to present methodology for the classification of potential psychotropic drugs on the basis of their activity. We first sketch the background of this class of drugs and then zoom in on so‐called pharmacoelectroencephalogram studies. These data pose some statistical challenges. For classification purposes, we propose a flexible hierarchical discriminant analysis tool, allowing us to take the specific nature of the drug class into account, as well as the features of the mixed models, in combination with fractional polynomials, fitted to the electroencephalogram data. The method is evaluated against the background of existing methods. The method's performance is studied by using a comprehensive analysis of a large electroencephalogram data set.