A plea for neutral comparison studies in computational sciences.
PLoS One
; 8(4): e61562, 2013.
Article
em En
| MEDLINE
| ID: mdl-23637855
ABSTRACT
In computational science literature including, e.g., bioinformatics, computational statistics or machine learning, most published articles are devoted to the development of "new methods", while comparison studies are generally appreciated by readers but surprisingly given poor consideration by many journals. This paper stresses the importance of neutral comparison studies for the objective evaluation of existing methods and the establishment of standards by drawing parallels with clinical research. The goal of the paper is twofold. Firstly, we present a survey of recent computational papers on supervised classification published in seven high-ranking computational science journals. The aim is to provide an up-to-date picture of current scientific practice with respect to the comparison of methods in both articles presenting new methods and articles focusing on the comparison study itself. Secondly, based on the results of our survey we critically discuss the necessity, impact and limitations of neutral comparison studies in computational sciences. We define three reasonable criteria a comparison study has to fulfill in order to be considered as neutral, and explicate general considerations on the individual components of a "tidy neutral comparison study". R codes for completely replicating our statistical analyses and figures are available from the companion website http//www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/020_professuren/boulesteix/plea2013.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Biologia Computacional
Tipo de estudo:
Guideline
/
Systematic_reviews
Limite:
Humans
Idioma:
En
Revista:
PLoS One
Assunto da revista:
CIENCIA
/
MEDICINA
Ano de publicação:
2013
Tipo de documento:
Article
País de afiliação:
Alemanha