BMC Med Inform Decis Mak 2021 May 4;21(Suppl 4):130. Epub 2021 May 4.
APHM, INSERM, IRD, Sciences Economiques & Sociales de la Sante & Traitement de l'Information Médicale (SESSTIM), Hop Timone, Biostatistique et Technologies de l'Information et de la Communication (BioSTIC), Aix Marseille Univ, Marseille, France.
Background: In high-dimensional data analysis, the complexity of predictive models can be reduced by selecting the most relevant features, which is crucial to reduce data noise and increase model accuracy and interpretability. Thus, in the field of clinical decision making, only the most relevant features from a set of medical descriptors should be considered when determining whether a patient is healthy or not. This statistical approach known as feature selection can be performed through regression or classification, in a supervised or unsupervised manner. Read More